Title string | Abstract string | Status string | User string | text string | label int64 | combined_text string | __index_level_0__ int64 |
|---|---|---|---|---|---|---|---|
Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications | This tutorial aims to introduce the fundamentals of adversarial robustness of
deep learning, presenting a well-structured review of up-to-date techniques to
assess the vulnerability of various types of deep learning models to
adversarial examples. This tutorial will particularly highlight
state-of-the-art techniques in... | Liked | zrz@andrew.cmu.edu | Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications : This tutorial aims to introduce the fundamentals of adversarial robustness of
deep learning, presenting a well-structured review of up-to-date techniques to
assess the vulnerability of various types of deep learning models to
adversarial ex... | 1 | zrz@andrew.cmu.edu [SEP] Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications : This tutorial aims to introduce the fundamentals of adversarial robustness of
deep learning, presenting a well-structured review of up-to-date techniques to
assess the vulnerability of various types of deep learning... | 205 |
Human-Like Active Learning: Machines Simulating the Human Learning Process | Although the use of active learning to increase learners' engagement has
recently been introduced in a variety of methods, empirical experiments are
lacking. In this study, we attempted to align two experiments in order to (1)
make a hypothesis for machine and (2) empirically confirm the effect of active
learning on le... | Disliked | zrz@andrew.cmu.edu | Human-Like Active Learning: Machines Simulating the Human Learning Process : Although the use of active learning to increase learners' engagement has
recently been introduced in a variety of methods, empirical experiments are
lacking. In this study, we attempted to align two experiments in order to (1)
make a hypothesi... | 0 | zrz@andrew.cmu.edu [SEP] Human-Like Active Learning: Machines Simulating the Human Learning Process : Although the use of active learning to increase learners' engagement has
recently been introduced in a variety of methods, empirical experiments are
lacking. In this study, we attempted to align two experiments in orde... | 128 |
Learning proofs for the classification of nilpotent semigroups | Machine learning is applied to find proofs, with smaller or smallest numbers
of nodes, for the classification of 4-nilpotent semigroups. | Disliked | zrz@andrew.cmu.edu | Learning proofs for the classification of nilpotent semigroups : Machine learning is applied to find proofs, with smaller or smallest numbers
of nodes, for the classification of 4-nilpotent semigroups. | 0 | zrz@andrew.cmu.edu [SEP] Learning proofs for the classification of nilpotent semigroups : Machine learning is applied to find proofs, with smaller or smallest numbers
of nodes, for the classification of 4-nilpotent semigroups. | 135 |
Flexible Morphing Aerial Robot with Inflatable Structure for Perching-based Human-Robot Interaction | Birds in nature perform perching not only for rest but also for interaction
with human such as the relationship with falconers. Recently, researchers
achieve perching-capable aerial robots as a way to save energy, and deformable
structure demonstrate significant advantages in efficiency of perching and
compactness of c... | Liked | jechoi@andrew.cmu.edu | Flexible Morphing Aerial Robot with Inflatable Structure for Perching-based Human-Robot Interaction : Birds in nature perform perching not only for rest but also for interaction
with human such as the relationship with falconers. Recently, researchers
achieve perching-capable aerial robots as a way to save energy, and ... | 1 | jechoi@andrew.cmu.edu [SEP] Flexible Morphing Aerial Robot with Inflatable Structure for Perching-based Human-Robot Interaction : Birds in nature perform perching not only for rest but also for interaction
with human such as the relationship with falconers. Recently, researchers
achieve perching-capable aerial robots a... | 525 |
Towards human-like kinematics in industrial robotic arms: a case study on a UR3 robot | Safety in industrial robotic environments is a hot research topic in the area
of human-robot interaction (HRI). Up to now, a robotic arm on an assembly line
interacts with other machines away from human workers. Nowadays, robotic arm
manufactures are aimed to their robots could increasingly perform tasks
collaborating ... | Liked | jechoi@andrew.cmu.edu | Towards human-like kinematics in industrial robotic arms: a case study on a UR3 robot : Safety in industrial robotic environments is a hot research topic in the area
of human-robot interaction (HRI). Up to now, a robotic arm on an assembly line
interacts with other machines away from human workers. Nowadays, robotic ar... | 1 | jechoi@andrew.cmu.edu [SEP] Towards human-like kinematics in industrial robotic arms: a case study on a UR3 robot : Safety in industrial robotic environments is a hot research topic in the area
of human-robot interaction (HRI). Up to now, a robotic arm on an assembly line
interacts with other machines away from human w... | 440 |
An Optimal Control View of Adversarial Machine Learning | I describe an optimal control view of adversarial machine learning, where the
dynamical system is the machine learner, the input are adversarial actions, and
the control costs are defined by the adversary's goals to do harm and be hard
to detect. This view encompasses many types of adversarial machine learning,
includi... | Disliked | zrz@andrew.cmu.edu | An Optimal Control View of Adversarial Machine Learning : I describe an optimal control view of adversarial machine learning, where the
dynamical system is the machine learner, the input are adversarial actions, and
the control costs are defined by the adversary's goals to do harm and be hard
to detect. This view encom... | 0 | zrz@andrew.cmu.edu [SEP] An Optimal Control View of Adversarial Machine Learning : I describe an optimal control view of adversarial machine learning, where the
dynamical system is the machine learner, the input are adversarial actions, and
the control costs are defined by the adversary's goals to do harm and be hard
t... | 27 |
Analyzing Fine-Grained Alignment and Enhancing Vision Understanding in Multimodal Language Models | Achieving better alignment between vision embeddings and Large Language
Models (LLMs) is crucial for enhancing the abilities of Multimodal LLMs
(MLLMs), particularly for recent models that rely on powerful pretrained vision
encoders and LLMs. A common approach to connect the pretrained vision encoder
and LLM is through... | Liked | zrz@andrew.cmu.edu | Analyzing Fine-Grained Alignment and Enhancing Vision Understanding in Multimodal Language Models : Achieving better alignment between vision embeddings and Large Language
Models (LLMs) is crucial for enhancing the abilities of Multimodal LLMs
(MLLMs), particularly for recent models that rely on powerful pretrained vis... | 1 | zrz@andrew.cmu.edu [SEP] Analyzing Fine-Grained Alignment and Enhancing Vision Understanding in Multimodal Language Models : Achieving better alignment between vision embeddings and Large Language
Models (LLMs) is crucial for enhancing the abilities of Multimodal LLMs
(MLLMs), particularly for recent models that rely o... | 376 |
Learning Human-arm Reaching Motion Using IMU in Human-Robot Collaboration | Many tasks performed by two humans require mutual interaction between arms
such as handing-over tools and objects. In order for a robotic arm to interact
with a human in the same way, it must reason about the location of the human
arm in real-time. Furthermore and to acquire interaction in a timely manner,
the robot mu... | Liked | jechoi@andrew.cmu.edu | Learning Human-arm Reaching Motion Using IMU in Human-Robot Collaboration : Many tasks performed by two humans require mutual interaction between arms
such as handing-over tools and objects. In order for a robotic arm to interact
with a human in the same way, it must reason about the location of the human
arm in real-t... | 1 | jechoi@andrew.cmu.edu [SEP] Learning Human-arm Reaching Motion Using IMU in Human-Robot Collaboration : Many tasks performed by two humans require mutual interaction between arms
such as handing-over tools and objects. In order for a robotic arm to interact
with a human in the same way, it must reason about the locatio... | 441 |
Adding Context to Source Code Representations for Deep Learning | Deep learning models have been successfully applied to a variety of software
engineering tasks, such as code classification, summarisation, and bug and
vulnerability detection. In order to apply deep learning to these tasks, source
code needs to be represented in a format that is suitable for input into the
deep learni... | Liked | zrz@andrew.cmu.edu | Adding Context to Source Code Representations for Deep Learning : Deep learning models have been successfully applied to a variety of software
engineering tasks, such as code classification, summarisation, and bug and
vulnerability detection. In order to apply deep learning to these tasks, source
code needs to be repre... | 1 | zrz@andrew.cmu.edu [SEP] Adding Context to Source Code Representations for Deep Learning : Deep learning models have been successfully applied to a variety of software
engineering tasks, such as code classification, summarisation, and bug and
vulnerability detection. In order to apply deep learning to these tasks, sour... | 246 |
Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-Training | Medical vision-and-language pre-training provides a feasible solution to
extract effective vision-and-language representations from medical images and
texts. However, few studies have been dedicated to this field to facilitate
medical vision-and-language understanding. In this paper, we propose a
self-supervised learni... | Liked | zrz@andrew.cmu.edu | Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-Training : Medical vision-and-language pre-training provides a feasible solution to
extract effective vision-and-language representations from medical images and
texts. However, few studies have been dedicated to this field to facilitate
medical vision... | 1 | zrz@andrew.cmu.edu [SEP] Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-Training : Medical vision-and-language pre-training provides a feasible solution to
extract effective vision-and-language representations from medical images and
texts. However, few studies have been dedicated to this field to ... | 367 |
Modern Deep Reinforcement Learning Algorithms | Recent advances in Reinforcement Learning, grounded on combining classical
theoretical results with Deep Learning paradigm, led to breakthroughs in many
artificial intelligence tasks and gave birth to Deep Reinforcement Learning
(DRL) as a field of research. In this work latest DRL algorithms are reviewed
with a focus ... | Liked | zrz@andrew.cmu.edu | Modern Deep Reinforcement Learning Algorithms : Recent advances in Reinforcement Learning, grounded on combining classical
theoretical results with Deep Learning paradigm, led to breakthroughs in many
artificial intelligence tasks and gave birth to Deep Reinforcement Learning
(DRL) as a field of research. In this work ... | 1 | zrz@andrew.cmu.edu [SEP] Modern Deep Reinforcement Learning Algorithms : Recent advances in Reinforcement Learning, grounded on combining classical
theoretical results with Deep Learning paradigm, led to breakthroughs in many
artificial intelligence tasks and gave birth to Deep Reinforcement Learning
(DRL) as a field o... | 212 |
An Introduction to MM Algorithms for Machine Learning and Statistical | MM (majorization--minimization) algorithms are an increasingly popular tool
for solving optimization problems in machine learning and statistical
estimation. This article introduces the MM algorithm framework in general and
via three popular example applications: Gaussian mixture regressions,
multinomial logistic regre... | Liked | zrz@andrew.cmu.edu | An Introduction to MM Algorithms for Machine Learning and Statistical : MM (majorization--minimization) algorithms are an increasingly popular tool
for solving optimization problems in machine learning and statistical
estimation. This article introduces the MM algorithm framework in general and
via three popular exampl... | 1 | zrz@andrew.cmu.edu [SEP] An Introduction to MM Algorithms for Machine Learning and Statistical : MM (majorization--minimization) algorithms are an increasingly popular tool
for solving optimization problems in machine learning and statistical
estimation. This article introduces the MM algorithm framework in general and... | 97 |
The SET Perceptual Factors Framework: Towards Assured Perception for Autonomous Systems | Future autonomous systems promise significant societal benefits, yet their
deployment raises concerns about safety and trustworthiness. A key concern is
assuring the reliability of robot perception, as perception seeds safe
decision-making. Failures in perception are often due to complex yet common
environmental factor... | Disliked | zrz@andrew.cmu.edu | The SET Perceptual Factors Framework: Towards Assured Perception for Autonomous Systems : Future autonomous systems promise significant societal benefits, yet their
deployment raises concerns about safety and trustworthiness. A key concern is
assuring the reliability of robot perception, as perception seeds safe
decisi... | 0 | zrz@andrew.cmu.edu [SEP] The SET Perceptual Factors Framework: Towards Assured Perception for Autonomous Systems : Future autonomous systems promise significant societal benefits, yet their
deployment raises concerns about safety and trustworthiness. A key concern is
assuring the reliability of robot perception, as per... | 299 |
Emotional Musical Prosody for the Enhancement of Trust in Robotic Arm Communication | As robotic arms become prevalent in industry it is crucial to improve levels
of trust from human collaborators. Low levels of trust in human-robot
interaction can reduce overall performance and prevent full robot utilization.
We investigated the potential benefits of using emotional musical prosody to
allow the robot t... | Disliked | jechoi@andrew.cmu.edu | Emotional Musical Prosody for the Enhancement of Trust in Robotic Arm Communication : As robotic arms become prevalent in industry it is crucial to improve levels
of trust from human collaborators. Low levels of trust in human-robot
interaction can reduce overall performance and prevent full robot utilization.
We inves... | 0 | jechoi@andrew.cmu.edu [SEP] Emotional Musical Prosody for the Enhancement of Trust in Robotic Arm Communication : As robotic arms become prevalent in industry it is crucial to improve levels
of trust from human collaborators. Low levels of trust in human-robot
interaction can reduce overall performance and prevent full... | 542 |
Generating Realistic Arm Movements in Reinforcement Learning: A Quantitative Comparison of Reward Terms and Task Requirements | The mimicking of human-like arm movement characteristics involves the
consideration of three factors during control policy synthesis: (a) chosen task
requirements, (b) inclusion of noise during movement execution and (c) chosen
optimality principles. Previous studies showed that when considering these
factors (a-c) ind... | Liked | jechoi@andrew.cmu.edu | Generating Realistic Arm Movements in Reinforcement Learning: A Quantitative Comparison of Reward Terms and Task Requirements : The mimicking of human-like arm movement characteristics involves the
consideration of three factors during control policy synthesis: (a) chosen task
requirements, (b) inclusion of noise durin... | 1 | jechoi@andrew.cmu.edu [SEP] Generating Realistic Arm Movements in Reinforcement Learning: A Quantitative Comparison of Reward Terms and Task Requirements : The mimicking of human-like arm movement characteristics involves the
consideration of three factors during control policy synthesis: (a) chosen task
requirements, ... | 571 |
A Unified Analytical Framework for Trustable Machine Learning and Automation Running with Blockchain | Traditional machine learning algorithms use data from databases that are
mutable, and therefore the data cannot be fully trusted. Also, the machine
learning process is difficult to automate. This paper proposes building a
trustable machine learning system by using blockchain technology, which can
store data in a perman... | Disliked | zrz@andrew.cmu.edu | A Unified Analytical Framework for Trustable Machine Learning and Automation Running with Blockchain : Traditional machine learning algorithms use data from databases that are
mutable, and therefore the data cannot be fully trusted. Also, the machine
learning process is difficult to automate. This paper proposes buildi... | 0 | zrz@andrew.cmu.edu [SEP] A Unified Analytical Framework for Trustable Machine Learning and Automation Running with Blockchain : Traditional machine learning algorithms use data from databases that are
mutable, and therefore the data cannot be fully trusted. Also, the machine
learning process is difficult to automate. T... | 35 |
A Survey of Deep Learning Techniques for Mobile Robot Applications | Advancements in deep learning over the years have attracted research into how
deep artificial neural networks can be used in robotic systems. This research
survey will present a summarization of the current research with a specific
focus on the gains and obstacles for deep learning to be applied to mobile
robotics. | Liked | zrz@andrew.cmu.edu | A Survey of Deep Learning Techniques for Mobile Robot Applications : Advancements in deep learning over the years have attracted research into how
deep artificial neural networks can be used in robotic systems. This research
survey will present a summarization of the current research with a specific
focus on the gains ... | 1 | zrz@andrew.cmu.edu [SEP] A Survey of Deep Learning Techniques for Mobile Robot Applications : Advancements in deep learning over the years have attracted research into how
deep artificial neural networks can be used in robotic systems. This research
survey will present a summarization of the current research with a spe... | 267 |
Moving Deep Learning into Web Browser: How Far Can We Go? | Recently, several JavaScript-based deep learning frameworks have emerged,
making it possible to perform deep learning tasks directly in browsers.
However, little is known on what and how well we can do with these frameworks
for deep learning in browsers. To bridge the knowledge gap, in this paper, we
conduct the first ... | Disliked | zrz@andrew.cmu.edu | Moving Deep Learning into Web Browser: How Far Can We Go? : Recently, several JavaScript-based deep learning frameworks have emerged,
making it possible to perform deep learning tasks directly in browsers.
However, little is known on what and how well we can do with these frameworks
for deep learning in browsers. To br... | 0 | zrz@andrew.cmu.edu [SEP] Moving Deep Learning into Web Browser: How Far Can We Go? : Recently, several JavaScript-based deep learning frameworks have emerged,
making it possible to perform deep learning tasks directly in browsers.
However, little is known on what and how well we can do with these frameworks
for deep le... | 164 |
Pre-training with Non-expert Human Demonstration for Deep Reinforcement Learning | Deep reinforcement learning (deep RL) has achieved superior performance in
complex sequential tasks by using deep neural networks as function
approximators to learn directly from raw input images. However, learning
directly from raw images is data inefficient. The agent must learn feature
representation of complex stat... | Liked | zrz@andrew.cmu.edu | Pre-training with Non-expert Human Demonstration for Deep Reinforcement Learning : Deep reinforcement learning (deep RL) has achieved superior performance in
complex sequential tasks by using deep neural networks as function
approximators to learn directly from raw input images. However, learning
directly from raw imag... | 1 | zrz@andrew.cmu.edu [SEP] Pre-training with Non-expert Human Demonstration for Deep Reinforcement Learning : Deep reinforcement learning (deep RL) has achieved superior performance in
complex sequential tasks by using deep neural networks as function
approximators to learn directly from raw input images. However, learni... | 260 |
Beyond One Model Fits All: Ensemble Deep Learning for Autonomous Vehicles | Deep learning has revolutionized autonomous driving by enabling vehicles to
perceive and interpret their surroundings with remarkable accuracy. This
progress is attributed to various deep learning models, including Mediated
Perception, Behavior Reflex, and Direct Perception, each offering unique
advantages and challeng... | Liked | zrz@andrew.cmu.edu | Beyond One Model Fits All: Ensemble Deep Learning for Autonomous Vehicles : Deep learning has revolutionized autonomous driving by enabling vehicles to
perceive and interpret their surroundings with remarkable accuracy. This
progress is attributed to various deep learning models, including Mediated
Perception, Behavior... | 1 | zrz@andrew.cmu.edu [SEP] Beyond One Model Fits All: Ensemble Deep Learning for Autonomous Vehicles : Deep learning has revolutionized autonomous driving by enabling vehicles to
perceive and interpret their surroundings with remarkable accuracy. This
progress is attributed to various deep learning models, including Medi... | 303 |
Deep Learning and Its Applications to Machine Health Monitoring: A Survey | Since 2006, deep learning (DL) has become a rapidly growing research
direction, redefining state-of-the-art performances in a wide range of areas
such as object recognition, image segmentation, speech recognition and machine
translation. In modern manufacturing systems, data-driven machine health
monitoring is gaining ... | Liked | zrz@andrew.cmu.edu | Deep Learning and Its Applications to Machine Health Monitoring: A Survey : Since 2006, deep learning (DL) has become a rapidly growing research
direction, redefining state-of-the-art performances in a wide range of areas
such as object recognition, image segmentation, speech recognition and machine
translation. In mod... | 1 | zrz@andrew.cmu.edu [SEP] Deep Learning and Its Applications to Machine Health Monitoring: A Survey : Since 2006, deep learning (DL) has become a rapidly growing research
direction, redefining state-of-the-art performances in a wide range of areas
such as object recognition, image segmentation, speech recognition and ma... | 240 |
Can Machines Learn the True Probabilities? | When there exists uncertainty, AI machines are designed to make decisions so
as to reach the best expected outcomes. Expectations are based on true facts
about the objective environment the machines interact with, and those facts can
be encoded into AI models in the form of true objective probability functions.
Accordi... | Liked | zrz@andrew.cmu.edu | Can Machines Learn the True Probabilities? : When there exists uncertainty, AI machines are designed to make decisions so
as to reach the best expected outcomes. Expectations are based on true facts
about the objective environment the machines interact with, and those facts can
be encoded into AI models in the form of ... | 1 | zrz@andrew.cmu.edu [SEP] Can Machines Learn the True Probabilities? : When there exists uncertainty, AI machines are designed to make decisions so
as to reach the best expected outcomes. Expectations are based on true facts
about the objective environment the machines interact with, and those facts can
be encoded into ... | 66 |
Teaching Computer Vision for Ecology | Computer vision can accelerate ecology research by automating the analysis of
raw imagery from sensors like camera traps, drones, and satellites. However,
computer vision is an emerging discipline that is rarely taught to ecologists.
This work discusses our experience teaching a diverse group of ecologists to
prototype... | Disliked | zrz@andrew.cmu.edu | Teaching Computer Vision for Ecology : Computer vision can accelerate ecology research by automating the analysis of
raw imagery from sensors like camera traps, drones, and satellites. However,
computer vision is an emerging discipline that is rarely taught to ecologists.
This work discusses our experience teaching a d... | 0 | zrz@andrew.cmu.edu [SEP] Teaching Computer Vision for Ecology : Computer vision can accelerate ecology research by automating the analysis of
raw imagery from sensors like camera traps, drones, and satellites. However,
computer vision is an emerging discipline that is rarely taught to ecologists.
This work discusses ou... | 375 |
Semantic-Aware Ship Detection with Vision-Language Integration | Ship detection in remote sensing imagery is a critical task with wide-ranging
applications, such as maritime activity monitoring, shipping logistics, and
environmental studies. However, existing methods often struggle to capture
fine-grained semantic information, limiting their effectiveness in complex
scenarios. To ad... | Liked | zrz@andrew.cmu.edu | Semantic-Aware Ship Detection with Vision-Language Integration : Ship detection in remote sensing imagery is a critical task with wide-ranging
applications, such as maritime activity monitoring, shipping logistics, and
environmental studies. However, existing methods often struggle to capture
fine-grained semantic info... | 1 | zrz@andrew.cmu.edu [SEP] Semantic-Aware Ship Detection with Vision-Language Integration : Ship detection in remote sensing imagery is a critical task with wide-ranging
applications, such as maritime activity monitoring, shipping logistics, and
environmental studies. However, existing methods often struggle to capture
f... | 347 |
When Machine Learning Meets Privacy: A Survey and Outlook | The newly emerged machine learning (e.g. deep learning) methods have become a
strong driving force to revolutionize a wide range of industries, such as smart
healthcare, financial technology, and surveillance systems. Meanwhile, privacy
has emerged as a big concern in this machine learning-based artificial
intelligence... | Disliked | zrz@andrew.cmu.edu | When Machine Learning Meets Privacy: A Survey and Outlook : The newly emerged machine learning (e.g. deep learning) methods have become a
strong driving force to revolutionize a wide range of industries, such as smart
healthcare, financial technology, and surveillance systems. Meanwhile, privacy
has emerged as a big co... | 0 | zrz@andrew.cmu.edu [SEP] When Machine Learning Meets Privacy: A Survey and Outlook : The newly emerged machine learning (e.g. deep learning) methods have become a
strong driving force to revolutionize a wide range of industries, such as smart
healthcare, financial technology, and surveillance systems. Meanwhile, privac... | 51 |
Machine Learning for Clinical Predictive Analytics | In this chapter, we provide a brief overview of applying machine learning
techniques for clinical prediction tasks. We begin with a quick introduction to
the concepts of machine learning and outline some of the most common machine
learning algorithms. Next, we demonstrate how to apply the algorithms with
appropriate to... | Disliked | zrz@andrew.cmu.edu | Machine Learning for Clinical Predictive Analytics : In this chapter, we provide a brief overview of applying machine learning
techniques for clinical prediction tasks. We begin with a quick introduction to
the concepts of machine learning and outline some of the most common machine
learning algorithms. Next, we demons... | 0 | zrz@andrew.cmu.edu [SEP] Machine Learning for Clinical Predictive Analytics : In this chapter, we provide a brief overview of applying machine learning
techniques for clinical prediction tasks. We begin with a quick introduction to
the concepts of machine learning and outline some of the most common machine
learning al... | 28 |
Enhancing camera surveillance using computer vision: a research note | $\mathbf{Purpose}$ - The growth of police operated surveillance cameras has
out-paced the ability of humans to monitor them effectively. Computer vision is
a possible solution. An ongoing research project on the application of computer
vision within a municipal police department is described. The paper aims to
discuss ... | Disliked | zrz@andrew.cmu.edu | Enhancing camera surveillance using computer vision: a research note : $\mathbf{Purpose}$ - The growth of police operated surveillance cameras has
out-paced the ability of humans to monitor them effectively. Computer vision is
a possible solution. An ongoing research project on the application of computer
vision within... | 0 | zrz@andrew.cmu.edu [SEP] Enhancing camera surveillance using computer vision: a research note : $\mathbf{Purpose}$ - The growth of police operated surveillance cameras has
out-paced the ability of humans to monitor them effectively. Computer vision is
a possible solution. An ongoing research project on the application ... | 343 |
Meta-Learning: A Survey | Meta-learning, or learning to learn, is the science of systematically
observing how different machine learning approaches perform on a wide range of
learning tasks, and then learning from this experience, or meta-data, to learn
new tasks much faster than otherwise possible. Not only does this dramatically
speed up and ... | Liked | zrz@andrew.cmu.edu | Meta-Learning: A Survey : Meta-learning, or learning to learn, is the science of systematically
observing how different machine learning approaches perform on a wide range of
learning tasks, and then learning from this experience, or meta-data, to learn
new tasks much faster than otherwise possible. Not only does this ... | 1 | zrz@andrew.cmu.edu [SEP] Meta-Learning: A Survey : Meta-learning, or learning to learn, is the science of systematically
observing how different machine learning approaches perform on a wide range of
learning tasks, and then learning from this experience, or meta-data, to learn
new tasks much faster than otherwise poss... | 87 |
Preparatory Manipulation Planning using Automatically Determined Single and Dual Arms | This paper presents a manipulation planning algorithm for robots to reorient
objects. It automatically finds a sequence of robot motion that manipulates and
prepares an object for specific tasks. Examples of the preparatory manipulation
planning problems include reorienting an electric drill to cut holes,
reorienting w... | Liked | jechoi@andrew.cmu.edu | Preparatory Manipulation Planning using Automatically Determined Single and Dual Arms : This paper presents a manipulation planning algorithm for robots to reorient
objects. It automatically finds a sequence of robot motion that manipulates and
prepares an object for specific tasks. Examples of the preparatory manipula... | 1 | jechoi@andrew.cmu.edu [SEP] Preparatory Manipulation Planning using Automatically Determined Single and Dual Arms : This paper presents a manipulation planning algorithm for robots to reorient
objects. It automatically finds a sequence of robot motion that manipulates and
prepares an object for specific tasks. Examples... | 496 |
Arm Manipulation Planning of Tethered Tools with the Help of a Tool Balancer | Robotic manipulation of tethered tools is widely seen in robotic work cells.
They may cause excess strain on the tool's cable or undesired entanglements
with the robot's arms. This paper presents a manipulation planner with cable
orientation constraints for tethered tools suspended by tool balancers. The
planner uses o... | Liked | jechoi@andrew.cmu.edu | Arm Manipulation Planning of Tethered Tools with the Help of a Tool Balancer : Robotic manipulation of tethered tools is widely seen in robotic work cells.
They may cause excess strain on the tool's cable or undesired entanglements
with the robot's arms. This paper presents a manipulation planner with cable
orientation... | 1 | jechoi@andrew.cmu.edu [SEP] Arm Manipulation Planning of Tethered Tools with the Help of a Tool Balancer : Robotic manipulation of tethered tools is widely seen in robotic work cells.
They may cause excess strain on the tool's cable or undesired entanglements
with the robot's arms. This paper presents a manipulation pl... | 529 |
Lidar for Autonomous Driving: The principles, challenges, and trends for automotive lidar and perception systems | Autonomous vehicles rely on their perception systems to acquire information
about their immediate surroundings. It is necessary to detect the presence of
other vehicles, pedestrians and other relevant entities. Safety concerns and
the need for accurate estimations have led to the introduction of Light
Detection and Ran... | Liked | zrz@andrew.cmu.edu | Lidar for Autonomous Driving: The principles, challenges, and trends for automotive lidar and perception systems : Autonomous vehicles rely on their perception systems to acquire information
about their immediate surroundings. It is necessary to detect the presence of
other vehicles, pedestrians and other relevant enti... | 1 | zrz@andrew.cmu.edu [SEP] Lidar for Autonomous Driving: The principles, challenges, and trends for automotive lidar and perception systems : Autonomous vehicles rely on their perception systems to acquire information
about their immediate surroundings. It is necessary to detect the presence of
other vehicles, pedestrian... | 296 |
Deep Gaussian Mixture Models | Deep learning is a hierarchical inference method formed by subsequent
multiple layers of learning able to more efficiently describe complex
relationships. In this work, Deep Gaussian Mixture Models are introduced and
discussed. A Deep Gaussian Mixture model (DGMM) is a network of multiple layers
of latent variables, wh... | Disliked | zrz@andrew.cmu.edu | Deep Gaussian Mixture Models : Deep learning is a hierarchical inference method formed by subsequent
multiple layers of learning able to more efficiently describe complex
relationships. In this work, Deep Gaussian Mixture Models are introduced and
discussed. A Deep Gaussian Mixture model (DGMM) is a network of multiple... | 0 | zrz@andrew.cmu.edu [SEP] Deep Gaussian Mixture Models : Deep learning is a hierarchical inference method formed by subsequent
multiple layers of learning able to more efficiently describe complex
relationships. In this work, Deep Gaussian Mixture Models are introduced and
discussed. A Deep Gaussian Mixture model (DGMM)... | 268 |
Experimental Characterization of Robot Arm Rigidity in Order to Be Used in Machining Operation | Attempts to install a rotating tool at the end of a robot arm
poly-articulated date back twenty years, but these robots were not designed for
that. Indeed, two essential features are necessary for machining: high rigidity
and precision in a given workspace. The experimental results presented are the
dynamic identificat... | Liked | jechoi@andrew.cmu.edu | Experimental Characterization of Robot Arm Rigidity in Order to Be Used in Machining Operation : Attempts to install a rotating tool at the end of a robot arm
poly-articulated date back twenty years, but these robots were not designed for
that. Indeed, two essential features are necessary for machining: high rigidity
a... | 1 | jechoi@andrew.cmu.edu [SEP] Experimental Characterization of Robot Arm Rigidity in Order to Be Used in Machining Operation : Attempts to install a rotating tool at the end of a robot arm
poly-articulated date back twenty years, but these robots were not designed for
that. Indeed, two essential features are necessary fo... | 526 |
WiCV 2020: The Seventh Women In Computer Vision Workshop | In this paper we present the details of Women in Computer Vision Workshop -
WiCV 2020, organized in alongside virtual CVPR 2020. This event aims at
encouraging the women researchers in the field of computer vision. It provides
a voice to a minority (female) group in computer vision community and focuses
on increasingly... | Disliked | zrz@andrew.cmu.edu | WiCV 2020: The Seventh Women In Computer Vision Workshop : In this paper we present the details of Women in Computer Vision Workshop -
WiCV 2020, organized in alongside virtual CVPR 2020. This event aims at
encouraging the women researchers in the field of computer vision. It provides
a voice to a minority (female) gro... | 0 | zrz@andrew.cmu.edu [SEP] WiCV 2020: The Seventh Women In Computer Vision Workshop : In this paper we present the details of Women in Computer Vision Workshop -
WiCV 2020, organized in alongside virtual CVPR 2020. This event aims at
encouraging the women researchers in the field of computer vision. It provides
a voice t... | 373 |
Kinematic Optimization of a Robotic Arm for Automation Tasks with Human Demonstration | Robotic arms are highly common in various automation processes such as
manufacturing lines. However, these highly capable robots are usually degraded
to simple repetitive tasks such as pick-and-place. On the other hand, designing
an optimal robot for one specific task consumes large resources of engineering
time and co... | Liked | jechoi@andrew.cmu.edu | Kinematic Optimization of a Robotic Arm for Automation Tasks with Human Demonstration : Robotic arms are highly common in various automation processes such as
manufacturing lines. However, these highly capable robots are usually degraded
to simple repetitive tasks such as pick-and-place. On the other hand, designing
an... | 1 | jechoi@andrew.cmu.edu [SEP] Kinematic Optimization of a Robotic Arm for Automation Tasks with Human Demonstration : Robotic arms are highly common in various automation processes such as
manufacturing lines. However, these highly capable robots are usually degraded
to simple repetitive tasks such as pick-and-place. On ... | 390 |
Public Perceptions of Autonomous Vehicles: A Survey of Pedestrians and Cyclists in Pittsburgh | This study investigates how autonomous vehicle(AV) technology is perceived by
pedestrians and bicyclists in Pittsburgh. Using survey data from over 1200
respondents, the research explores the interplay between demographics, AV
interactions, infrastructural readiness, safety perceptions, and trust.
Findings highlight de... | Liked | zrz@andrew.cmu.edu | Public Perceptions of Autonomous Vehicles: A Survey of Pedestrians and Cyclists in Pittsburgh : This study investigates how autonomous vehicle(AV) technology is perceived by
pedestrians and bicyclists in Pittsburgh. Using survey data from over 1200
respondents, the research explores the interplay between demographics, ... | 1 | zrz@andrew.cmu.edu [SEP] Public Perceptions of Autonomous Vehicles: A Survey of Pedestrians and Cyclists in Pittsburgh : This study investigates how autonomous vehicle(AV) technology is perceived by
pedestrians and bicyclists in Pittsburgh. Using survey data from over 1200
respondents, the research explores the interpl... | 301 |
Reflective VLM Planning for Dual-Arm Desktop Cleaning: Bridging Open-Vocabulary Perception and Precise Manipulation | Desktop cleaning demands open-vocabulary recognition and precise manipulation
for heterogeneous debris. We propose a hierarchical framework integrating
reflective Vision-Language Model (VLM) planning with dual-arm execution via
structured scene representation. Grounded-SAM2 facilitates open-vocabulary
detection, while ... | Liked | jechoi@andrew.cmu.edu | Reflective VLM Planning for Dual-Arm Desktop Cleaning: Bridging Open-Vocabulary Perception and Precise Manipulation : Desktop cleaning demands open-vocabulary recognition and precise manipulation
for heterogeneous debris. We propose a hierarchical framework integrating
reflective Vision-Language Model (VLM) planning wi... | 1 | jechoi@andrew.cmu.edu [SEP] Reflective VLM Planning for Dual-Arm Desktop Cleaning: Bridging Open-Vocabulary Perception and Precise Manipulation : Desktop cleaning demands open-vocabulary recognition and precise manipulation
for heterogeneous debris. We propose a hierarchical framework integrating
reflective Vision-Lang... | 556 |
DAG-Plan: Generating Directed Acyclic Dependency Graphs for Dual-Arm Cooperative Planning | Dual-arm robots offer enhanced versatility and efficiency over single-arm
counterparts by enabling concurrent manipulation of multiple objects or
cooperative execution of tasks using both arms. However, the coordination of
dual-arm systems for long-horizon tasks continues to pose significant
challenges, stemming from t... | Liked | jechoi@andrew.cmu.edu | DAG-Plan: Generating Directed Acyclic Dependency Graphs for Dual-Arm Cooperative Planning : Dual-arm robots offer enhanced versatility and efficiency over single-arm
counterparts by enabling concurrent manipulation of multiple objects or
cooperative execution of tasks using both arms. However, the coordination of
dual-... | 1 | jechoi@andrew.cmu.edu [SEP] DAG-Plan: Generating Directed Acyclic Dependency Graphs for Dual-Arm Cooperative Planning : Dual-arm robots offer enhanced versatility and efficiency over single-arm
counterparts by enabling concurrent manipulation of multiple objects or
cooperative execution of tasks using both arms. Howeve... | 487 |
Pen and Paper Exercises in Machine Learning | This is a collection of (mostly) pen-and-paper exercises in machine learning.
The exercises are on the following topics: linear algebra, optimisation,
directed graphical models, undirected graphical models, expressive power of
graphical models, factor graphs and message passing, inference for hidden
Markov models, mode... | Disliked | zrz@andrew.cmu.edu | Pen and Paper Exercises in Machine Learning : This is a collection of (mostly) pen-and-paper exercises in machine learning.
The exercises are on the following topics: linear algebra, optimisation,
directed graphical models, undirected graphical models, expressive power of
graphical models, factor graphs and message pas... | 0 | zrz@andrew.cmu.edu [SEP] Pen and Paper Exercises in Machine Learning : This is a collection of (mostly) pen-and-paper exercises in machine learning.
The exercises are on the following topics: linear algebra, optimisation,
directed graphical models, undirected graphical models, expressive power of
graphical models, fact... | 122 |
How to deal with glare for improved perception of Autonomous Vehicles | Vision sensors are versatile and can capture a wide range of visual cues,
such as color, texture, shape, and depth. This versatility, along with the
relatively inexpensive availability of machine vision cameras, played an
important role in adopting vision-based environment perception systems in
autonomous vehicles (AVs... | Liked | zrz@andrew.cmu.edu | How to deal with glare for improved perception of Autonomous Vehicles : Vision sensors are versatile and can capture a wide range of visual cues,
such as color, texture, shape, and depth. This versatility, along with the
relatively inexpensive availability of machine vision cameras, played an
important role in adopting... | 1 | zrz@andrew.cmu.edu [SEP] How to deal with glare for improved perception of Autonomous Vehicles : Vision sensors are versatile and can capture a wide range of visual cues,
such as color, texture, shape, and depth. This versatility, along with the
relatively inexpensive availability of machine vision cameras, played an
i... | 300 |
Multiband NFC for High-Throughput Wireless Computer Vision Sensor Network | Vision sensors lie in the heart of computer vision. In many computer vision
applications, such as AR/VR, non-contacting near-field communication (NFC) with
high throughput is required to transfer information to algorithms. In this
work, we proposed a novel NFC system which utilizes multiple frequency bands to
achieve h... | Liked | zrz@andrew.cmu.edu | Multiband NFC for High-Throughput Wireless Computer Vision Sensor Network : Vision sensors lie in the heart of computer vision. In many computer vision
applications, such as AR/VR, non-contacting near-field communication (NFC) with
high throughput is required to transfer information to algorithms. In this
work, we prop... | 1 | zrz@andrew.cmu.edu [SEP] Multiband NFC for High-Throughput Wireless Computer Vision Sensor Network : Vision sensors lie in the heart of computer vision. In many computer vision
applications, such as AR/VR, non-contacting near-field communication (NFC) with
high throughput is required to transfer information to algorith... | 337 |
PACC: A Passive-Arm Approach for High-Payload Collaborative Carrying with Quadruped Robots Using Model Predictive Control | In this paper, we introduce the concept of using passive arm structures with
intrinsic impedance for robot-robot and human-robot collaborative carrying with
quadruped robots. The concept is meant for a leader-follower task and takes a
minimalist approach that focuses on exploiting the robots' payload capabilities
and r... | Disliked | jechoi@andrew.cmu.edu | PACC: A Passive-Arm Approach for High-Payload Collaborative Carrying with Quadruped Robots Using Model Predictive Control : In this paper, we introduce the concept of using passive arm structures with
intrinsic impedance for robot-robot and human-robot collaborative carrying with
quadruped robots. The concept is meant ... | 0 | jechoi@andrew.cmu.edu [SEP] PACC: A Passive-Arm Approach for High-Payload Collaborative Carrying with Quadruped Robots Using Model Predictive Control : In this paper, we introduce the concept of using passive arm structures with
intrinsic impedance for robot-robot and human-robot collaborative carrying with
quadruped r... | 23 |
Tuning Learning Rates with the Cumulative-Learning Constant | This paper introduces a novel method for optimizing learning rates in machine
learning. A previously unrecognized proportionality between learning rates and
dataset sizes is discovered, providing valuable insights into how dataset scale
influences training dynamics. Additionally, a cumulative learning constant is
ident... | Liked | zrz@andrew.cmu.edu | Tuning Learning Rates with the Cumulative-Learning Constant : This paper introduces a novel method for optimizing learning rates in machine
learning. A previously unrecognized proportionality between learning rates and
dataset sizes is discovered, providing valuable insights into how dataset scale
influences training d... | 1 | zrz@andrew.cmu.edu [SEP] Tuning Learning Rates with the Cumulative-Learning Constant : This paper introduces a novel method for optimizing learning rates in machine
learning. A previously unrecognized proportionality between learning rates and
dataset sizes is discovered, providing valuable insights into how dataset sc... | 43 |
Multi-agent Collaborative Perception for Robotic Fleet: A Systematic Review | Collaborative perception in multi-robot fleets is a way to incorporate the
power of unity in robotic fleets. Collaborative perception refers to the
collective ability of multiple entities or agents to share and integrate their
sensory information for a more comprehensive understanding of their
environment. In other wor... | Liked | zrz@andrew.cmu.edu | Multi-agent Collaborative Perception for Robotic Fleet: A Systematic Review : Collaborative perception in multi-robot fleets is a way to incorporate the
power of unity in robotic fleets. Collaborative perception refers to the
collective ability of multiple entities or agents to share and integrate their
sensory informa... | 1 | zrz@andrew.cmu.edu [SEP] Multi-agent Collaborative Perception for Robotic Fleet: A Systematic Review : Collaborative perception in multi-robot fleets is a way to incorporate the
power of unity in robotic fleets. Collaborative perception refers to the
collective ability of multiple entities or agents to share and integr... | 279 |
V-MAO: Generative Modeling for Multi-Arm Manipulation of Articulated Objects | Manipulating articulated objects requires multiple robot arms in general. It
is challenging to enable multiple robot arms to collaboratively complete
manipulation tasks on articulated objects. In this paper, we present
$\textbf{V-MAO}$, a framework for learning multi-arm manipulation of
articulated objects. Our framewo... | Liked | jechoi@andrew.cmu.edu | V-MAO: Generative Modeling for Multi-Arm Manipulation of Articulated Objects : Manipulating articulated objects requires multiple robot arms in general. It
is challenging to enable multiple robot arms to collaboratively complete
manipulation tasks on articulated objects. In this paper, we present
$\textbf{V-MAO}$, a fr... | 1 | jechoi@andrew.cmu.edu [SEP] V-MAO: Generative Modeling for Multi-Arm Manipulation of Articulated Objects : Manipulating articulated objects requires multiple robot arms in general. It
is challenging to enable multiple robot arms to collaboratively complete
manipulation tasks on articulated objects. In this paper, we pr... | 498 |
Deep Embedding Kernel | In this paper, we propose a novel supervised learning method that is called
Deep Embedding Kernel (DEK). DEK combines the advantages of deep learning and
kernel methods in a unified framework. More specifically, DEK is a learnable
kernel represented by a newly designed deep architecture. Compared with
pre-defined kerne... | Disliked | zrz@andrew.cmu.edu | Deep Embedding Kernel : In this paper, we propose a novel supervised learning method that is called
Deep Embedding Kernel (DEK). DEK combines the advantages of deep learning and
kernel methods in a unified framework. More specifically, DEK is a learnable
kernel represented by a newly designed deep architecture. Compare... | 0 | zrz@andrew.cmu.edu [SEP] Deep Embedding Kernel : In this paper, we propose a novel supervised learning method that is called
Deep Embedding Kernel (DEK). DEK combines the advantages of deep learning and
kernel methods in a unified framework. More specifically, DEK is a learnable
kernel represented by a newly designed d... | 215 |
Development of an Intuitive Foot-Machine Interface for Robotic Surgery | The human-machine interface is of critical importance for master-slave
control of the robotic system for surgery, in which current systems offer the
control or two robotic arms teleoperated by the surgeon's hands. To relax the
need for surgical assistants and augment dexterity in surgery, it has been
recently proposed ... | Liked | jechoi@andrew.cmu.edu | Development of an Intuitive Foot-Machine Interface for Robotic Surgery : The human-machine interface is of critical importance for master-slave
control of the robotic system for surgery, in which current systems offer the
control or two robotic arms teleoperated by the surgeon's hands. To relax the
need for surgical as... | 1 | jechoi@andrew.cmu.edu [SEP] Development of an Intuitive Foot-Machine Interface for Robotic Surgery : The human-machine interface is of critical importance for master-slave
control of the robotic system for surgery, in which current systems offer the
control or two robotic arms teleoperated by the surgeon's hands. To re... | 483 |
Domain Knowledge in Artificial Intelligence: Using Conceptual Modeling to Increase Machine Learning Accuracy and Explainability | Machine learning enables the extraction of useful information from large,
diverse datasets. However, despite many successful applications, machine
learning continues to suffer from performance and transparency issues. These
challenges can be partially attributed to the limited use of domain knowledge
by machine learnin... | Liked | zrz@andrew.cmu.edu | Domain Knowledge in Artificial Intelligence: Using Conceptual Modeling to Increase Machine Learning Accuracy and Explainability : Machine learning enables the extraction of useful information from large,
diverse datasets. However, despite many successful applications, machine
learning continues to suffer from performan... | 1 | zrz@andrew.cmu.edu [SEP] Domain Knowledge in Artificial Intelligence: Using Conceptual Modeling to Increase Machine Learning Accuracy and Explainability : Machine learning enables the extraction of useful information from large,
diverse datasets. However, despite many successful applications, machine
learning continues... | 116 |
Neurofeedback-Driven 6-DOF Robotic Arm: Integration of Brain-Computer Interface with Arduino for Advanced Control | Brain computer interface (BCI) applications in robotics are becoming more
famous and famous. People with disabilities are facing a real-time problem of
doing simple activities such as grasping, handshaking etc. in order to aid with
this problem, the use of brain signals to control actuators is showing a great
importanc... | Liked | jechoi@andrew.cmu.edu | Neurofeedback-Driven 6-DOF Robotic Arm: Integration of Brain-Computer Interface with Arduino for Advanced Control : Brain computer interface (BCI) applications in robotics are becoming more
famous and famous. People with disabilities are facing a real-time problem of
doing simple activities such as grasping, handshakin... | 1 | jechoi@andrew.cmu.edu [SEP] Neurofeedback-Driven 6-DOF Robotic Arm: Integration of Brain-Computer Interface with Arduino for Advanced Control : Brain computer interface (BCI) applications in robotics are becoming more
famous and famous. People with disabilities are facing a real-time problem of
doing simple activities ... | 448 |
One-Shot Dual-Arm Imitation Learning | We introduce One-Shot Dual-Arm Imitation Learning (ODIL), which enables
dual-arm robots to learn precise and coordinated everyday tasks from just a
single demonstration of the task. ODIL uses a new three-stage visual servoing
(3-VS) method for precise alignment between the end-effector and target object,
after which re... | Liked | jechoi@andrew.cmu.edu | One-Shot Dual-Arm Imitation Learning : We introduce One-Shot Dual-Arm Imitation Learning (ODIL), which enables
dual-arm robots to learn precise and coordinated everyday tasks from just a
single demonstration of the task. ODIL uses a new three-stage visual servoing
(3-VS) method for precise alignment between the end-eff... | 1 | jechoi@andrew.cmu.edu [SEP] One-Shot Dual-Arm Imitation Learning : We introduce One-Shot Dual-Arm Imitation Learning (ODIL), which enables
dual-arm robots to learn precise and coordinated everyday tasks from just a
single demonstration of the task. ODIL uses a new three-stage visual servoing
(3-VS) method for precise a... | 443 |
Harnessing The Multi-Stability Of Kresling Origami For Reconfigurable Articulation In Soft Robotic Arms | This study examines a biology-inspired approach of using reconfigurable
articulation to reduce the control requirement for soft robotic arms. We
construct a robotic arm by assembling Kresling origami modules that exhibit
predictable bistability. Via switching between their two stable states, these
origami modules can b... | Liked | jechoi@andrew.cmu.edu | Harnessing The Multi-Stability Of Kresling Origami For Reconfigurable Articulation In Soft Robotic Arms : This study examines a biology-inspired approach of using reconfigurable
articulation to reduce the control requirement for soft robotic arms. We
construct a robotic arm by assembling Kresling origami modules that e... | 1 | jechoi@andrew.cmu.edu [SEP] Harnessing The Multi-Stability Of Kresling Origami For Reconfigurable Articulation In Soft Robotic Arms : This study examines a biology-inspired approach of using reconfigurable
articulation to reduce the control requirement for soft robotic arms. We
construct a robotic arm by assembling Kre... | 484 |
Survey on LiDAR Perception in Adverse Weather Conditions | Autonomous vehicles rely on a variety of sensors to gather information about
their surrounding. The vehicle's behavior is planned based on the environment
perception, making its reliability crucial for safety reasons. The active LiDAR
sensor is able to create an accurate 3D representation of a scene, making it a
valuab... | Disliked | zrz@andrew.cmu.edu | Survey on LiDAR Perception in Adverse Weather Conditions : Autonomous vehicles rely on a variety of sensors to gather information about
their surrounding. The vehicle's behavior is planned based on the environment
perception, making its reliability crucial for safety reasons. The active LiDAR
sensor is able to create a... | 0 | zrz@andrew.cmu.edu [SEP] Survey on LiDAR Perception in Adverse Weather Conditions : Autonomous vehicles rely on a variety of sensors to gather information about
their surrounding. The vehicle's behavior is planned based on the environment
perception, making its reliability crucial for safety reasons. The active LiDAR
s... | 334 |
Interruption-Aware Cooperative Perception for V2X Communication-Aided Autonomous Driving | Cooperative perception can significantly improve the perception performance
of autonomous vehicles beyond the limited perception ability of individual
vehicles by exchanging information with neighbor agents through V2X
communication. However, most existing work assume ideal communication among
agents, ignoring the sign... | Liked | zrz@andrew.cmu.edu | Interruption-Aware Cooperative Perception for V2X Communication-Aided Autonomous Driving : Cooperative perception can significantly improve the perception performance
of autonomous vehicles beyond the limited perception ability of individual
vehicles by exchanging information with neighbor agents through V2X
communicat... | 1 | zrz@andrew.cmu.edu [SEP] Interruption-Aware Cooperative Perception for V2X Communication-Aided Autonomous Driving : Cooperative perception can significantly improve the perception performance
of autonomous vehicles beyond the limited perception ability of individual
vehicles by exchanging information with neighbor agen... | 285 |
Bridging Hard and Soft: Mechanical Metamaterials Enable Rigid Torque Transmission in Soft Robots | Torque and continuous rotation are fundamental methods of actuation and
manipulation in rigid robots. Soft robot arms use soft materials and structures
to mimic the passive compliance of biological arms that bend and extend. This
use of compliance prevents soft arms from continuously transmitting and
exerting torques t... | Liked | jechoi@andrew.cmu.edu | Bridging Hard and Soft: Mechanical Metamaterials Enable Rigid Torque Transmission in Soft Robots : Torque and continuous rotation are fundamental methods of actuation and
manipulation in rigid robots. Soft robot arms use soft materials and structures
to mimic the passive compliance of biological arms that bend and exte... | 1 | jechoi@andrew.cmu.edu [SEP] Bridging Hard and Soft: Mechanical Metamaterials Enable Rigid Torque Transmission in Soft Robots : Torque and continuous rotation are fundamental methods of actuation and
manipulation in rigid robots. Soft robot arms use soft materials and structures
to mimic the passive compliance of biolog... | 407 |
Autonomous Soil Collection in Environments With Heterogeneous Terrain | To autonomously collect soil in uncultivated terrain, robotic arms must
distinguish between different amorphous materials and submerge themselves into
the correct material. We develop a prototype that collects soil in
heterogeneous terrain. If mounted to a mobile robot, it can be used to perform
soil collection and ana... | Liked | jechoi@andrew.cmu.edu | Autonomous Soil Collection in Environments With Heterogeneous Terrain : To autonomously collect soil in uncultivated terrain, robotic arms must
distinguish between different amorphous materials and submerge themselves into
the correct material. We develop a prototype that collects soil in
heterogeneous terrain. If moun... | 1 | jechoi@andrew.cmu.edu [SEP] Autonomous Soil Collection in Environments With Heterogeneous Terrain : To autonomously collect soil in uncultivated terrain, robotic arms must
distinguish between different amorphous materials and submerge themselves into
the correct material. We develop a prototype that collects soil in
he... | 519 |
Open Arms: Open-Source Arms, Hands & Control | Open Arms is a novel open-source platform of realistic human-like robotic
hands and arms hardware with 28 Degree-of-Freedom (DoF), designed to extend the
capabilities and accessibility of humanoid robotic grasping and manipulation.
The Open Arms framework includes an open SDK and development environment,
simulation too... | Liked | jechoi@andrew.cmu.edu | Open Arms: Open-Source Arms, Hands & Control : Open Arms is a novel open-source platform of realistic human-like robotic
hands and arms hardware with 28 Degree-of-Freedom (DoF), designed to extend the
capabilities and accessibility of humanoid robotic grasping and manipulation.
The Open Arms framework includes an open ... | 1 | jechoi@andrew.cmu.edu [SEP] Open Arms: Open-Source Arms, Hands & Control : Open Arms is a novel open-source platform of realistic human-like robotic
hands and arms hardware with 28 Degree-of-Freedom (DoF), designed to extend the
capabilities and accessibility of humanoid robotic grasping and manipulation.
The Open Arms... | 434 |
Deep frequency principle towards understanding why deeper learning is faster | Understanding the effect of depth in deep learning is a critical problem. In
this work, we utilize the Fourier analysis to empirically provide a promising
mechanism to understand why feedforward deeper learning is faster. To this end,
we separate a deep neural network, trained by normal stochastic gradient
descent, int... | Liked | zrz@andrew.cmu.edu | Deep frequency principle towards understanding why deeper learning is faster : Understanding the effect of depth in deep learning is a critical problem. In
this work, we utilize the Fourier analysis to empirically provide a promising
mechanism to understand why feedforward deeper learning is faster. To this end,
we sep... | 1 | zrz@andrew.cmu.edu [SEP] Deep frequency principle towards understanding why deeper learning is faster : Understanding the effect of depth in deep learning is a critical problem. In
this work, we utilize the Fourier analysis to empirically provide a promising
mechanism to understand why feedforward deeper learning is fa... | 194 |
RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins | In the rapidly advancing field of robotics, dual-arm coordination and complex
object manipulation are essential capabilities for developing advanced
autonomous systems. However, the scarcity of diverse, high-quality
demonstration data and real-world-aligned evaluation benchmarks severely limits
such development. To add... | Liked | jechoi@andrew.cmu.edu | RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins : In the rapidly advancing field of robotics, dual-arm coordination and complex
object manipulation are essential capabilities for developing advanced
autonomous systems. However, the scarcity of diverse, high-quality
demonstration data and real-world-ali... | 1 | jechoi@andrew.cmu.edu [SEP] RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins : In the rapidly advancing field of robotics, dual-arm coordination and complex
object manipulation are essential capabilities for developing advanced
autonomous systems. However, the scarcity of diverse, high-quality
demonstra... | 511 |
Planning to Build Soma Blocks Using a Dual-arm Robot | This paper presents a planner that can automatically find an optimal assembly
sequence for a dual-arm robot to assemble the soma blocks. The planner uses the
mesh model of objects and the final state of the assembly to generate all
possible assembly sequence and evaluate the optimal assembly sequence by
considering the... | Liked | jechoi@andrew.cmu.edu | Planning to Build Soma Blocks Using a Dual-arm Robot : This paper presents a planner that can automatically find an optimal assembly
sequence for a dual-arm robot to assemble the soma blocks. The planner uses the
mesh model of objects and the final state of the assembly to generate all
possible assembly sequence and ev... | 1 | jechoi@andrew.cmu.edu [SEP] Planning to Build Soma Blocks Using a Dual-arm Robot : This paper presents a planner that can automatically find an optimal assembly
sequence for a dual-arm robot to assemble the soma blocks. The planner uses the
mesh model of objects and the final state of the assembly to generate all
possi... | 497 |
Cybathlon -- Legged Mobile Assistance for Quadriplegics | Assistance robots are the future for people who need daily care due to
limited mobility or being wheelchair-bound. Current solutions of attaching
robotic arms to motorized wheelchairs only provide limited additional mobility
at the cost of increased size. We present a mouth joystick control interface,
augmented with vo... | Disliked | jechoi@andrew.cmu.edu | Cybathlon -- Legged Mobile Assistance for Quadriplegics : Assistance robots are the future for people who need daily care due to
limited mobility or being wheelchair-bound. Current solutions of attaching
robotic arms to motorized wheelchairs only provide limited additional mobility
at the cost of increased size. We pre... | 0 | jechoi@andrew.cmu.edu [SEP] Cybathlon -- Legged Mobile Assistance for Quadriplegics : Assistance robots are the future for people who need daily care due to
limited mobility or being wheelchair-bound. Current solutions of attaching
robotic arms to motorized wheelchairs only provide limited additional mobility
at the co... | 524 |
RGB-D Robotic Pose Estimation For a Servicing Robotic Arm | A large number of robotic and human-assisted missions to the Moon and Mars
are forecast. NASA's efforts to learn about the geology and makeup of these
celestial bodies rely heavily on the use of robotic arms. The safety and
redundancy aspects will be crucial when humans will be working alongside the
robotic explorers. ... | Liked | jechoi@andrew.cmu.edu | RGB-D Robotic Pose Estimation For a Servicing Robotic Arm : A large number of robotic and human-assisted missions to the Moon and Mars
are forecast. NASA's efforts to learn about the geology and makeup of these
celestial bodies rely heavily on the use of robotic arms. The safety and
redundancy aspects will be crucial w... | 1 | jechoi@andrew.cmu.edu [SEP] RGB-D Robotic Pose Estimation For a Servicing Robotic Arm : A large number of robotic and human-assisted missions to the Moon and Mars
are forecast. NASA's efforts to learn about the geology and makeup of these
celestial bodies rely heavily on the use of robotic arms. The safety and
redundan... | 449 |
Optimal Multi-Manipulator Arm Placement for Maximal Dexterity during Robotics Surgery | Robot arm placements are oftentimes a limitation in surgical preoperative
procedures, relying on trained staff to evaluate and decide on the optimal
positions for the arms. Given new and different patient anatomies, it can be
challenging to make an informed choice, leading to more frequently colliding
arms or limited m... | Liked | jechoi@andrew.cmu.edu | Optimal Multi-Manipulator Arm Placement for Maximal Dexterity during Robotics Surgery : Robot arm placements are oftentimes a limitation in surgical preoperative
procedures, relying on trained staff to evaluate and decide on the optimal
positions for the arms. Given new and different patient anatomies, it can be
challe... | 1 | jechoi@andrew.cmu.edu [SEP] Optimal Multi-Manipulator Arm Placement for Maximal Dexterity during Robotics Surgery : Robot arm placements are oftentimes a limitation in surgical preoperative
procedures, relying on trained staff to evaluate and decide on the optimal
positions for the arms. Given new and different patient... | 553 |
Developing and Comparing Single-arm and Dual-arm Regrasp | The goal of this paper is to develop efficient regrasp algorithms for
single-arm and dual-arm regrasp and compares the performance of single-arm and
dual-arm regrasp by running the two algorithms thousands of times. We focus on
pick-and-place regrasp which reorients an object from one placement to another
by using a se... | Liked | jechoi@andrew.cmu.edu | Developing and Comparing Single-arm and Dual-arm Regrasp : The goal of this paper is to develop efficient regrasp algorithms for
single-arm and dual-arm regrasp and compares the performance of single-arm and
dual-arm regrasp by running the two algorithms thousands of times. We focus on
pick-and-place regrasp which reor... | 1 | jechoi@andrew.cmu.edu [SEP] Developing and Comparing Single-arm and Dual-arm Regrasp : The goal of this paper is to develop efficient regrasp algorithms for
single-arm and dual-arm regrasp and compares the performance of single-arm and
dual-arm regrasp by running the two algorithms thousands of times. We focus on
pick-... | 8 |
Words or Vision: Do Vision-Language Models Have Blind Faith in Text? | Vision-Language Models (VLMs) excel in integrating visual and textual
information for vision-centric tasks, but their handling of inconsistencies
between modalities is underexplored. We investigate VLMs' modality preferences
when faced with visual data and varied textual inputs in vision-centered
settings. By introduci... | Disliked | zrz@andrew.cmu.edu | Words or Vision: Do Vision-Language Models Have Blind Faith in Text? : Vision-Language Models (VLMs) excel in integrating visual and textual
information for vision-centric tasks, but their handling of inconsistencies
between modalities is underexplored. We investigate VLMs' modality preferences
when faced with visual d... | 0 | zrz@andrew.cmu.edu [SEP] Words or Vision: Do Vision-Language Models Have Blind Faith in Text? : Vision-Language Models (VLMs) excel in integrating visual and textual
information for vision-centric tasks, but their handling of inconsistencies
between modalities is underexplored. We investigate VLMs' modality preferences... | 351 |
3D Hand-Eye Calibration for Collaborative Robot Arm: Look at Robot Base Once | Hand-eye calibration is a common problem in the field of collaborative
robotics, involving the determination of the transformation matrix between the
visual sensor and the robot flange to enable vision-based robotic tasks.
However, this process typically requires multiple movements of the robot arm
and an external cali... | Liked | jechoi@andrew.cmu.edu | 3D Hand-Eye Calibration for Collaborative Robot Arm: Look at Robot Base Once : Hand-eye calibration is a common problem in the field of collaborative
robotics, involving the determination of the transformation matrix between the
visual sensor and the robot flange to enable vision-based robotic tasks.
However, this proc... | 1 | jechoi@andrew.cmu.edu [SEP] 3D Hand-Eye Calibration for Collaborative Robot Arm: Look at Robot Base Once : Hand-eye calibration is a common problem in the field of collaborative
robotics, involving the determination of the transformation matrix between the
visual sensor and the robot flange to enable vision-based robot... | 495 |
Beneficial and Harmful Explanatory Machine Learning | Given the recent successes of Deep Learning in AI there has been increased
interest in the role and need for explanations in machine learned theories. A
distinct notion in this context is that of Michie's definition of Ultra-Strong
Machine Learning (USML). USML is demonstrated by a measurable increase in human
performa... | Liked | zrz@andrew.cmu.edu | Beneficial and Harmful Explanatory Machine Learning : Given the recent successes of Deep Learning in AI there has been increased
interest in the role and need for explanations in machine learned theories. A
distinct notion in this context is that of Michie's definition of Ultra-Strong
Machine Learning (USML). USML is d... | 1 | zrz@andrew.cmu.edu [SEP] Beneficial and Harmful Explanatory Machine Learning : Given the recent successes of Deep Learning in AI there has been increased
interest in the role and need for explanations in machine learned theories. A
distinct notion in this context is that of Michie's definition of Ultra-Strong
Machine L... | 126 |
Optimal Trajectory Planning for Flexible Robots with Large Deformation | Robot arms with lighter weight can reduce unnecessary energy consumption
which is desirable in robotic industry. However, lightweight arms undergo
undesirable elastic deformation. In this paper, the planar motion of a
lightweight flexible arm is investigated. In order to obtain a precise
mathematical model, the axial d... | Liked | jechoi@andrew.cmu.edu | Optimal Trajectory Planning for Flexible Robots with Large Deformation : Robot arms with lighter weight can reduce unnecessary energy consumption
which is desirable in robotic industry. However, lightweight arms undergo
undesirable elastic deformation. In this paper, the planar motion of a
lightweight flexible arm is i... | 1 | jechoi@andrew.cmu.edu [SEP] Optimal Trajectory Planning for Flexible Robots with Large Deformation : Robot arms with lighter weight can reduce unnecessary energy consumption
which is desirable in robotic industry. However, lightweight arms undergo
undesirable elastic deformation. In this paper, the planar motion of a
l... | 572 |
Application of deep reinforcement learning for Indian stock trading automation | In stock trading, feature extraction and trading strategy design are the two
important tasks to achieve long-term benefits using machine learning
techniques. Several methods have been proposed to design trading strategy by
acquiring trading signals to maximize the rewards. In the present paper the
theory of deep reinfo... | Liked | zrz@andrew.cmu.edu | Application of deep reinforcement learning for Indian stock trading automation : In stock trading, feature extraction and trading strategy design are the two
important tasks to achieve long-term benefits using machine learning
techniques. Several methods have been proposed to design trading strategy by
acquiring tradin... | 1 | zrz@andrew.cmu.edu [SEP] Application of deep reinforcement learning for Indian stock trading automation : In stock trading, feature extraction and trading strategy design are the two
important tasks to achieve long-term benefits using machine learning
techniques. Several methods have been proposed to design trading str... | 219 |
Dynamic Movement Primitive based Motion Retargeting for Dual-Arm Sign Language Motions | We aim to develop an efficient programming method for equipping service
robots with the skill of performing sign language motions. This paper addresses
the problem of transferring complex dual-arm sign language motions
characterized by the coordination among arms and hands from human to robot,
which is seldom considere... | Liked | jechoi@andrew.cmu.edu | Dynamic Movement Primitive based Motion Retargeting for Dual-Arm Sign Language Motions : We aim to develop an efficient programming method for equipping service
robots with the skill of performing sign language motions. This paper addresses
the problem of transferring complex dual-arm sign language motions
characterize... | 1 | jechoi@andrew.cmu.edu [SEP] Dynamic Movement Primitive based Motion Retargeting for Dual-Arm Sign Language Motions : We aim to develop an efficient programming method for equipping service
robots with the skill of performing sign language motions. This paper addresses
the problem of transferring complex dual-arm sign l... | 489 |
An Overview of Deep Semi-Supervised Learning | Deep neural networks demonstrated their ability to provide remarkable
performances on a wide range of supervised learning tasks (e.g., image
classification) when trained on extensive collections of labeled data (e.g.,
ImageNet). However, creating such large datasets requires a considerable amount
of resources, time, an... | Liked | zrz@andrew.cmu.edu | An Overview of Deep Semi-Supervised Learning : Deep neural networks demonstrated their ability to provide remarkable
performances on a wide range of supervised learning tasks (e.g., image
classification) when trained on extensive collections of labeled data (e.g.,
ImageNet). However, creating such large datasets requir... | 1 | zrz@andrew.cmu.edu [SEP] An Overview of Deep Semi-Supervised Learning : Deep neural networks demonstrated their ability to provide remarkable
performances on a wide range of supervised learning tasks (e.g., image
classification) when trained on extensive collections of labeled data (e.g.,
ImageNet). However, creating s... | 200 |
Task Oriented Video Coding: A Survey | Video coding technology has been continuously improved for higher compression
ratio with higher resolution. However, the state-of-the-art video coding
standards, such as H.265/HEVC and Versatile Video Coding, are still designed
with the assumption the compressed video will be watched by humans. With the
tremendous adva... | Disliked | zrz@andrew.cmu.edu | Task Oriented Video Coding: A Survey : Video coding technology has been continuously improved for higher compression
ratio with higher resolution. However, the state-of-the-art video coding
standards, such as H.265/HEVC and Versatile Video Coding, are still designed
with the assumption the compressed video will be watc... | 0 | zrz@andrew.cmu.edu [SEP] Task Oriented Video Coding: A Survey : Video coding technology has been continuously improved for higher compression
ratio with higher resolution. However, the state-of-the-art video coding
standards, such as H.265/HEVC and Versatile Video Coding, are still designed
with the assumption the comp... | 354 |
How Developers Iterate on Machine Learning Workflows -- A Survey of the Applied Machine Learning Literature | Machine learning workflow development is anecdotally regarded to be an
iterative process of trial-and-error with humans-in-the-loop. However, we are
not aware of quantitative evidence corroborating this popular belief. A
quantitative characterization of iteration can serve as a benchmark for machine
learning workflow d... | Liked | zrz@andrew.cmu.edu | How Developers Iterate on Machine Learning Workflows -- A Survey of the Applied Machine Learning Literature : Machine learning workflow development is anecdotally regarded to be an
iterative process of trial-and-error with humans-in-the-loop. However, we are
not aware of quantitative evidence corroborating this popular... | 1 | zrz@andrew.cmu.edu [SEP] How Developers Iterate on Machine Learning Workflows -- A Survey of the Applied Machine Learning Literature : Machine learning workflow development is anecdotally regarded to be an
iterative process of trial-and-error with humans-in-the-loop. However, we are
not aware of quantitative evidence c... | 108 |
Learning Task-aware Robust Deep Learning Systems | Many works demonstrate that deep learning system is vulnerable to adversarial
attack. A deep learning system consists of two parts: the deep learning task
and the deep model. Nowadays, most existing works investigate the impact of the
deep model on robustness of deep learning systems, ignoring the impact of the
learnin... | Liked | zrz@andrew.cmu.edu | Learning Task-aware Robust Deep Learning Systems : Many works demonstrate that deep learning system is vulnerable to adversarial
attack. A deep learning system consists of two parts: the deep learning task
and the deep model. Nowadays, most existing works investigate the impact of the
deep model on robustness of deep l... | 1 | zrz@andrew.cmu.edu [SEP] Learning Task-aware Robust Deep Learning Systems : Many works demonstrate that deep learning system is vulnerable to adversarial
attack. A deep learning system consists of two parts: the deep learning task
and the deep model. Nowadays, most existing works investigate the impact of the
deep mode... | 162 |
To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software | Autonomous vehicle perception typically relies on modular pipelines that
decompose the task into detection, tracking, and prediction. While
interpretable, these pipelines suffer from error accumulation and limited
inter-task synergy. Unified perception has emerged as a promising paradigm that
integrates these sub-tasks... | Disliked | zrz@andrew.cmu.edu | To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software : Autonomous vehicle perception typically relies on modular pipelines that
decompose the task into detection, tracking, and prediction. While
interpretable, these pipelines suffer from error accumulation and limited
inter-task synergy. Uni... | 0 | zrz@andrew.cmu.edu [SEP] To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Software : Autonomous vehicle perception typically relies on modular pipelines that
decompose the task into detection, tracking, and prediction. While
interpretable, these pipelines suffer from error accumulation and limite... | 335 |
Advances in Hybrid Modular Climbing Robots: Design Principles and Refinement Strategies | This paper explores the design strategies for hybrid pole- or trunk-climbing
robots, focusing on methods to inform design decisions and assess metrics such
as adaptability and performance. A wheeled-grasping hybrid robot with modular,
tendon-driven grasping arms and a wheeled drive system mounted on a turret was
develo... | Liked | jechoi@andrew.cmu.edu | Advances in Hybrid Modular Climbing Robots: Design Principles and Refinement Strategies : This paper explores the design strategies for hybrid pole- or trunk-climbing
robots, focusing on methods to inform design decisions and assess metrics such
as adaptability and performance. A wheeled-grasping hybrid robot with modu... | 1 | jechoi@andrew.cmu.edu [SEP] Advances in Hybrid Modular Climbing Robots: Design Principles and Refinement Strategies : This paper explores the design strategies for hybrid pole- or trunk-climbing
robots, focusing on methods to inform design decisions and assess metrics such
as adaptability and performance. A wheeled-gra... | 564 |
Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolbox | With the breakthrough of AlphaGo, deep reinforcement learning becomes a
recognized technique for solving sequential decision-making problems. Despite
its reputation, data inefficiency caused by its trial and error learning
mechanism makes deep reinforcement learning hard to be practical in a wide
range of areas. Plenty... | Disliked | zrz@andrew.cmu.edu | Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolbox : With the breakthrough of AlphaGo, deep reinforcement learning becomes a
recognized technique for solving sequential decision-making problems. Despite
its reputation, data inefficiency caused by its trial and error learni... | 0 | zrz@andrew.cmu.edu [SEP] Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolbox : With the breakthrough of AlphaGo, deep reinforcement learning becomes a
recognized technique for solving sequential decision-making problems. Despite
its reputation, data inefficiency caused by i... | 179 |
Evaluation Challenges for Geospatial ML | As geospatial machine learning models and maps derived from their predictions
are increasingly used for downstream analyses in science and policy, it is
imperative to evaluate their accuracy and applicability. Geospatial machine
learning has key distinctions from other learning paradigms, and as such, the
correct way t... | Disliked | zrz@andrew.cmu.edu | Evaluation Challenges for Geospatial ML : As geospatial machine learning models and maps derived from their predictions
are increasingly used for downstream analyses in science and policy, it is
imperative to evaluate their accuracy and applicability. Geospatial machine
learning has key distinctions from other learning... | 0 | zrz@andrew.cmu.edu [SEP] Evaluation Challenges for Geospatial ML : As geospatial machine learning models and maps derived from their predictions
are increasingly used for downstream analyses in science and policy, it is
imperative to evaluate their accuracy and applicability. Geospatial machine
learning has key distinc... | 52 |
A Mobile Quad-Arm Robot ARMS: Wheeled-Legged Tripedal Locomotion and Quad-Arm Loco-Manipulation | This article proposes a mobile quad-arm robot: ARMS, which unifies
wheeled-legged tripedal locomotion, wheeled locomotion, and quad-arm
loco-manipulation. ARMS's four arms have different mechanisms and are partially
designed to be general-purpose arms for the hybrid locomotion and
loco-manipulation. One three-degree-of... | Disliked | jechoi@andrew.cmu.edu | A Mobile Quad-Arm Robot ARMS: Wheeled-Legged Tripedal Locomotion and Quad-Arm Loco-Manipulation : This article proposes a mobile quad-arm robot: ARMS, which unifies
wheeled-legged tripedal locomotion, wheeled locomotion, and quad-arm
loco-manipulation. ARMS's four arms have different mechanisms and are partially
design... | 0 | jechoi@andrew.cmu.edu [SEP] A Mobile Quad-Arm Robot ARMS: Wheeled-Legged Tripedal Locomotion and Quad-Arm Loco-Manipulation : This article proposes a mobile quad-arm robot: ARMS, which unifies
wheeled-legged tripedal locomotion, wheeled locomotion, and quad-arm
loco-manipulation. ARMS's four arms have different mechani... | 15 |
Highly dynamic locomotion control of biped robot enhanced by swing arms | Swing arms have an irreplaceable role in promoting highly dynamic locomotion
on bipedal robots by a larger angular momentum control space from the viewpoint
of biomechanics. Few bipedal robots utilize swing arms and its redundancy
characteristic of multiple degrees of freedom due to the lack of appropriate
locomotion c... | Disliked | jechoi@andrew.cmu.edu | Highly dynamic locomotion control of biped robot enhanced by swing arms : Swing arms have an irreplaceable role in promoting highly dynamic locomotion
on bipedal robots by a larger angular momentum control space from the viewpoint
of biomechanics. Few bipedal robots utilize swing arms and its redundancy
characteristic ... | 0 | jechoi@andrew.cmu.edu [SEP] Highly dynamic locomotion control of biped robot enhanced by swing arms : Swing arms have an irreplaceable role in promoting highly dynamic locomotion
on bipedal robots by a larger angular momentum control space from the viewpoint
of biomechanics. Few bipedal robots utilize swing arms and it... | 425 |
Geometrization of deep networks for the interpretability of deep learning systems | How to understand deep learning systems remains an open problem. In this
paper we propose that the answer may lie in the geometrization of deep
networks. Geometrization is a bridge to connect physics, geometry, deep network
and quantum computation and this may result in a new scheme to reveal the rule
of the physical w... | Disliked | zrz@andrew.cmu.edu | Geometrization of deep networks for the interpretability of deep learning systems : How to understand deep learning systems remains an open problem. In this
paper we propose that the answer may lie in the geometrization of deep
networks. Geometrization is a bridge to connect physics, geometry, deep network
and quantum ... | 0 | zrz@andrew.cmu.edu [SEP] Geometrization of deep networks for the interpretability of deep learning systems : How to understand deep learning systems remains an open problem. In this
paper we propose that the answer may lie in the geometrization of deep
networks. Geometrization is a bridge to connect physics, geometry, ... | 160 |
Position Paper: Towards Transparent Machine Learning | Transparent machine learning is introduced as an alternative form of machine
learning, where both the model and the learning system are represented in
source code form. The goal of this project is to enable direct human
understanding of machine learning models, giving us the ability to learn,
verify, and refine them as... | Liked | zrz@andrew.cmu.edu | Position Paper: Towards Transparent Machine Learning : Transparent machine learning is introduced as an alternative form of machine
learning, where both the model and the learning system are represented in
source code form. The goal of this project is to enable direct human
understanding of machine learning models, giv... | 1 | zrz@andrew.cmu.edu [SEP] Position Paper: Towards Transparent Machine Learning : Transparent machine learning is introduced as an alternative form of machine
learning, where both the model and the learning system are represented in
source code form. The goal of this project is to enable direct human
understanding of mac... | 31 |
Deep Learning: From Basics to Building Deep Neural Networks with Python | This book is intended for beginners who have no familiarity with deep
learning. Our only expectation from readers is that they already have the basic
programming skills in Python. | Disliked | zrz@andrew.cmu.edu | Deep Learning: From Basics to Building Deep Neural Networks with Python : This book is intended for beginners who have no familiarity with deep
learning. Our only expectation from readers is that they already have the basic
programming skills in Python. | 0 | zrz@andrew.cmu.edu [SEP] Deep Learning: From Basics to Building Deep Neural Networks with Python : This book is intended for beginners who have no familiarity with deep
learning. Our only expectation from readers is that they already have the basic
programming skills in Python. | 202 |
Automating the Learning of Inverse Kinematics for Robotic Arms with Redundant DoFs | Inverse Kinematics (IK) solves the problem of mapping from the Cartesian
space to the joint configuration space of a robotic arm. It has a wide range of
applications in areas such as computer graphics, protein structure prediction,
and robotics. With the vast advances of artificial neural networks (NNs), many
researche... | Liked | jechoi@andrew.cmu.edu | Automating the Learning of Inverse Kinematics for Robotic Arms with Redundant DoFs : Inverse Kinematics (IK) solves the problem of mapping from the Cartesian
space to the joint configuration space of a robotic arm. It has a wide range of
applications in areas such as computer graphics, protein structure prediction,
and... | 1 | jechoi@andrew.cmu.edu [SEP] Automating the Learning of Inverse Kinematics for Robotic Arms with Redundant DoFs : Inverse Kinematics (IK) solves the problem of mapping from the Cartesian
space to the joint configuration space of a robotic arm. It has a wide range of
applications in areas such as computer graphics, prote... | 455 |
Classic machine learning methods | In this chapter, we present the main classic machine learning methods. A
large part of the chapter is devoted to supervised learning techniques for
classification and regression, including nearest-neighbor methods, linear and
logistic regressions, support vector machines and tree-based algorithms. We
also describe the ... | Disliked | zrz@andrew.cmu.edu | Classic machine learning methods : In this chapter, we present the main classic machine learning methods. A
large part of the chapter is devoted to supervised learning techniques for
classification and regression, including nearest-neighbor methods, linear and
logistic regressions, support vector machines and tree-base... | 0 | zrz@andrew.cmu.edu [SEP] Classic machine learning methods : In this chapter, we present the main classic machine learning methods. A
large part of the chapter is devoted to supervised learning techniques for
classification and regression, including nearest-neighbor methods, linear and
logistic regressions, support vect... | 123 |
Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task | Concurrent perception datasets for autonomous driving are mainly limited to
frontal view with sensors mounted on the vehicle. None of them is designed for
the overlooked roadside perception tasks. On the other hand, the data captured
from roadside cameras have strengths over frontal-view data, which is believed
to faci... | Disliked | zrz@andrew.cmu.edu | Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task : Concurrent perception datasets for autonomous driving are mainly limited to
frontal view with sensors mounted on the vehicle. None of them is designed for
the overlooked roadside perception tasks. On the other hand, t... | 0 | zrz@andrew.cmu.edu [SEP] Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task : Concurrent perception datasets for autonomous driving are mainly limited to
frontal view with sensors mounted on the vehicle. None of them is designed for
the overlooked roadside perception ta... | 304 |
A metric for characterizing the arm nonuse workspace in poststroke individuals using a robot arm | An over-reliance on the less-affected limb for functional tasks at the
expense of the paretic limb and in spite of recovered capacity is an
often-observed phenomenon in survivors of hemispheric stroke. The difference
between capacity for use and actual spontaneous use is referred to as arm
nonuse. Obtaining an ecologic... | Liked | jechoi@andrew.cmu.edu | A metric for characterizing the arm nonuse workspace in poststroke individuals using a robot arm : An over-reliance on the less-affected limb for functional tasks at the
expense of the paretic limb and in spite of recovered capacity is an
often-observed phenomenon in survivors of hemispheric stroke. The difference
betw... | 1 | jechoi@andrew.cmu.edu [SEP] A metric for characterizing the arm nonuse workspace in poststroke individuals using a robot arm : An over-reliance on the less-affected limb for functional tasks at the
expense of the paretic limb and in spite of recovered capacity is an
often-observed phenomenon in survivors of hemispheric... | 410 |
Probabilistic Deep Learning with Probabilistic Neural Networks and Deep Probabilistic Models | Probabilistic deep learning is deep learning that accounts for uncertainty,
both model uncertainty and data uncertainty. It is based on the use of
probabilistic models and deep neural networks. We distinguish two approaches to
probabilistic deep learning: probabilistic neural networks and deep
probabilistic models. The... | Liked | zrz@andrew.cmu.edu | Probabilistic Deep Learning with Probabilistic Neural Networks and Deep Probabilistic Models : Probabilistic deep learning is deep learning that accounts for uncertainty,
both model uncertainty and data uncertainty. It is based on the use of
probabilistic models and deep neural networks. We distinguish two approaches t... | 1 | zrz@andrew.cmu.edu [SEP] Probabilistic Deep Learning with Probabilistic Neural Networks and Deep Probabilistic Models : Probabilistic deep learning is deep learning that accounts for uncertainty,
both model uncertainty and data uncertainty. It is based on the use of
probabilistic models and deep neural networks. We dis... | 169 |
A Survey on Resilient Machine Learning | Machine learning based system are increasingly being used for sensitive tasks
such as security surveillance, guiding autonomous vehicle, taking investment
decisions, detecting and blocking network intrusion and malware etc. However,
recent research has shown that machine learning models are venerable to attacks
by adve... | Liked | zrz@andrew.cmu.edu | A Survey on Resilient Machine Learning : Machine learning based system are increasingly being used for sensitive tasks
such as security surveillance, guiding autonomous vehicle, taking investment
decisions, detecting and blocking network intrusion and malware etc. However,
recent research has shown that machine learnin... | 1 | zrz@andrew.cmu.edu [SEP] A Survey on Resilient Machine Learning : Machine learning based system are increasingly being used for sensitive tasks
such as security surveillance, guiding autonomous vehicle, taking investment
decisions, detecting and blocking network intrusion and malware etc. However,
recent research has s... | 96 |
Security of Deep Learning Methodologies: Challenges and Opportunities | Despite the plethora of studies about security vulnerabilities and defenses
of deep learning models, security aspects of deep learning methodologies, such
as transfer learning, have been rarely studied. In this article, we highlight
the security challenges and research opportunities of these methodologies,
focusing on ... | Liked | zrz@andrew.cmu.edu | Security of Deep Learning Methodologies: Challenges and Opportunities : Despite the plethora of studies about security vulnerabilities and defenses
of deep learning models, security aspects of deep learning methodologies, such
as transfer learning, have been rarely studied. In this article, we highlight
the security ch... | 1 | zrz@andrew.cmu.edu [SEP] Security of Deep Learning Methodologies: Challenges and Opportunities : Despite the plethora of studies about security vulnerabilities and defenses
of deep learning models, security aspects of deep learning methodologies, such
as transfer learning, have been rarely studied. In this article, we ... | 265 |
Expanding the Boundaries of Vision Prior Knowledge in Multi-modal Large Language Models | Does the prior knowledge of the vision encoder constrain the capability
boundary of Multi-modal Large Language Models (MLLMs)? While most existing
research treats MLLMs as unified systems optimized through end-to-end training,
the impact of vision encoder's prior knowledge is seldom investigated. In this
work, we intro... | Liked | zrz@andrew.cmu.edu | Expanding the Boundaries of Vision Prior Knowledge in Multi-modal Large Language Models : Does the prior knowledge of the vision encoder constrain the capability
boundary of Multi-modal Large Language Models (MLLMs)? While most existing
research treats MLLMs as unified systems optimized through end-to-end training,
the... | 1 | zrz@andrew.cmu.edu [SEP] Expanding the Boundaries of Vision Prior Knowledge in Multi-modal Large Language Models : Does the prior knowledge of the vision encoder constrain the capability
boundary of Multi-modal Large Language Models (MLLMs)? While most existing
research treats MLLMs as unified systems optimized through... | 348 |
Neural Models and Algorithms for Sensorimotor Control of an Octopus Arm | In this article, a biophysically realistic model of a soft octopus arm with
internal musculature is presented. The modeling is motivated by experimental
observations of sensorimotor control where an arm localizes and reaches a
target. Major contributions of this article are: (i) development of models to
capture the mec... | Liked | jechoi@andrew.cmu.edu | Neural Models and Algorithms for Sensorimotor Control of an Octopus Arm : In this article, a biophysically realistic model of a soft octopus arm with
internal musculature is presented. The modeling is motivated by experimental
observations of sensorimotor control where an arm localizes and reaches a
target. Major contr... | 1 | jechoi@andrew.cmu.edu [SEP] Neural Models and Algorithms for Sensorimotor Control of an Octopus Arm : In this article, a biophysically realistic model of a soft octopus arm with
internal musculature is presented. The modeling is motivated by experimental
observations of sensorimotor control where an arm localizes and r... | 493 |
PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python | Machine learning is a general-purpose technology holding promises for many
interdisciplinary research problems. However, significant barriers exist in
crossing disciplinary boundaries when most machine learning tools are developed
in different areas separately. We present Pykale - a Python library for
knowledge-aware m... | Disliked | zrz@andrew.cmu.edu | PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python : Machine learning is a general-purpose technology holding promises for many
interdisciplinary research problems. However, significant barriers exist in
crossing disciplinary boundaries when most machine learning tools are developed
in different a... | 0 | zrz@andrew.cmu.edu [SEP] PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python : Machine learning is a general-purpose technology holding promises for many
interdisciplinary research problems. However, significant barriers exist in
crossing disciplinary boundaries when most machine learning tools are... | 136 |
Improving Cancer Imaging Diagnosis with Bayesian Networks and Deep Learning: A Bayesian Deep Learning Approach | With recent advancements in the development of artificial intelligence
applications using theories and algorithms in machine learning, many accurate
models can be created to train and predict on given datasets. With the
realization of the importance of imaging interpretation in cancer diagnosis,
this article aims to in... | Liked | zrz@andrew.cmu.edu | Improving Cancer Imaging Diagnosis with Bayesian Networks and Deep Learning: A Bayesian Deep Learning Approach : With recent advancements in the development of artificial intelligence
applications using theories and algorithms in machine learning, many accurate
models can be created to train and predict on given datase... | 1 | zrz@andrew.cmu.edu [SEP] Improving Cancer Imaging Diagnosis with Bayesian Networks and Deep Learning: A Bayesian Deep Learning Approach : With recent advancements in the development of artificial intelligence
applications using theories and algorithms in machine learning, many accurate
models can be created to train an... | 217 |
Pre-training with Non-expert Human Demonstration for Deep Reinforcement Learning | Deep reinforcement learning (deep RL) has achieved superior performance in
complex sequential tasks by using deep neural networks as function
approximators to learn directly from raw input images. However, learning
directly from raw images is data inefficient. The agent must learn feature
representation of complex stat... | Liked | zrz@andrew.cmu.edu | Pre-training with Non-expert Human Demonstration for Deep Reinforcement Learning : Deep reinforcement learning (deep RL) has achieved superior performance in
complex sequential tasks by using deep neural networks as function
approximators to learn directly from raw input images. However, learning
directly from raw imag... | 1 | zrz@andrew.cmu.edu [SEP] Pre-training with Non-expert Human Demonstration for Deep Reinforcement Learning : Deep reinforcement learning (deep RL) has achieved superior performance in
complex sequential tasks by using deep neural networks as function
approximators to learn directly from raw input images. However, learni... | 266 |
Generating and Customizing Robotic Arm Trajectories using Neural Networks | We introduce a neural network approach for generating and customizing the
trajectory of a robotic arm, that guarantees precision and repeatability. To
highlight the potential of this novel method, we describe the design and
implementation of the technique and show its application in an experimental
setting of cognitive... | Liked | jechoi@andrew.cmu.edu | Generating and Customizing Robotic Arm Trajectories using Neural Networks : We introduce a neural network approach for generating and customizing the
trajectory of a robotic arm, that guarantees precision and repeatability. To
highlight the potential of this novel method, we describe the design and
implementation of th... | 1 | jechoi@andrew.cmu.edu [SEP] Generating and Customizing Robotic Arm Trajectories using Neural Networks : We introduce a neural network approach for generating and customizing the
trajectory of a robotic arm, that guarantees precision and repeatability. To
highlight the potential of this novel method, we describe the des... | 454 |
Pedipulate: Enabling Manipulation Skills using a Quadruped Robot's Leg | Legged robots have the potential to become vital in maintenance, home
support, and exploration scenarios. In order to interact with and manipulate
their environments, most legged robots are equipped with a dedicated robot arm,
which means additional mass and mechanical complexity compared to standard
legged robots. In ... | Liked | jechoi@andrew.cmu.edu | Pedipulate: Enabling Manipulation Skills using a Quadruped Robot's Leg : Legged robots have the potential to become vital in maintenance, home
support, and exploration scenarios. In order to interact with and manipulate
their environments, most legged robots are equipped with a dedicated robot arm,
which means addition... | 1 | jechoi@andrew.cmu.edu [SEP] Pedipulate: Enabling Manipulation Skills using a Quadruped Robot's Leg : Legged robots have the potential to become vital in maintenance, home
support, and exploration scenarios. In order to interact with and manipulate
their environments, most legged robots are equipped with a dedicated rob... | 533 |
Augmented Reality Remote Operation of Dual Arm Manipulators in Hot Boxes | In nuclear isotope and chemistry laboratories, hot cells and gloveboxes
provide scientists with a controlled and safe environment to perform
experiments. Working on experiments in these isolated containment cells
requires scientists to be physically present. For hot cell work today,
scientists manipulate equipment and ... | Liked | jechoi@andrew.cmu.edu | Augmented Reality Remote Operation of Dual Arm Manipulators in Hot Boxes : In nuclear isotope and chemistry laboratories, hot cells and gloveboxes
provide scientists with a controlled and safe environment to perform
experiments. Working on experiments in these isolated containment cells
requires scientists to be physic... | 1 | jechoi@andrew.cmu.edu [SEP] Augmented Reality Remote Operation of Dual Arm Manipulators in Hot Boxes : In nuclear isotope and chemistry laboratories, hot cells and gloveboxes
provide scientists with a controlled and safe environment to perform
experiments. Working on experiments in these isolated containment cells
requ... | 521 |
Communicating Robot Arm Motion Intent Through Mixed Reality Head-mounted Displays | Efficient motion intent communication is necessary for safe and collaborative
work environments with collocated humans and robots. Humans efficiently
communicate their motion intent to other humans through gestures, gaze, and
social cues. However, robots often have difficulty efficiently communicating
their motion inte... | Liked | jechoi@andrew.cmu.edu | Communicating Robot Arm Motion Intent Through Mixed Reality Head-mounted Displays : Efficient motion intent communication is necessary for safe and collaborative
work environments with collocated humans and robots. Humans efficiently
communicate their motion intent to other humans through gestures, gaze, and
social cue... | 1 | jechoi@andrew.cmu.edu [SEP] Communicating Robot Arm Motion Intent Through Mixed Reality Head-mounted Displays : Efficient motion intent communication is necessary for safe and collaborative
work environments with collocated humans and robots. Humans efficiently
communicate their motion intent to other humans through ge... | 561 |
The ART of Transfer Learning: An Adaptive and Robust Pipeline | Transfer learning is an essential tool for improving the performance of
primary tasks by leveraging information from auxiliary data resources. In this
work, we propose Adaptive Robust Transfer Learning (ART), a flexible pipeline
of performing transfer learning with generic machine learning algorithms. We
establish the ... | Liked | zrz@andrew.cmu.edu | The ART of Transfer Learning: An Adaptive and Robust Pipeline : Transfer learning is an essential tool for improving the performance of
primary tasks by leveraging information from auxiliary data resources. In this
work, we propose Adaptive Robust Transfer Learning (ART), a flexible pipeline
of performing transfer lear... | 1 | zrz@andrew.cmu.edu [SEP] The ART of Transfer Learning: An Adaptive and Robust Pipeline : Transfer learning is an essential tool for improving the performance of
primary tasks by leveraging information from auxiliary data resources. In this
work, we propose Adaptive Robust Transfer Learning (ART), a flexible pipeline
of... | 151 |
APEX: Ambidextrous Dual-Arm Robotic Manipulation Using Collision-Free Generative Diffusion Models | Dexterous manipulation, particularly adept coordinating and grasping,
constitutes a fundamental and indispensable capability for robots, facilitating
the emulation of human-like behaviors. Integrating this capability into robots
empowers them to supplement and even supplant humans in undertaking
increasingly intricate ... | Liked | jechoi@andrew.cmu.edu | APEX: Ambidextrous Dual-Arm Robotic Manipulation Using Collision-Free Generative Diffusion Models : Dexterous manipulation, particularly adept coordinating and grasping,
constitutes a fundamental and indispensable capability for robots, facilitating
the emulation of human-like behaviors. Integrating this capability int... | 1 | jechoi@andrew.cmu.edu [SEP] APEX: Ambidextrous Dual-Arm Robotic Manipulation Using Collision-Free Generative Diffusion Models : Dexterous manipulation, particularly adept coordinating and grasping,
constitutes a fundamental and indispensable capability for robots, facilitating
the emulation of human-like behaviors. Int... | 494 |
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