Title string | Abstract string | Status string | User string | text string | label int64 | combined_text string | __index_level_0__ int64 |
|---|---|---|---|---|---|---|---|
Temporal-related Convolutional-Restricted-Boltzmann-Machine capable of learning relational order via reinforcement learning procedure? | In this article, we extend the conventional framework of
convolutional-Restricted-Boltzmann-Machine to learn highly abstract features
among abitrary number of time related input maps by constructing a layer of
multiplicative units, which capture the relations among inputs. In many cases,
more than two maps are strongly... | Disliked | zrz@andrew.cmu.edu | Temporal-related Convolutional-Restricted-Boltzmann-Machine capable of learning relational order via reinforcement learning procedure? : In this article, we extend the conventional framework of
convolutional-Restricted-Boltzmann-Machine to learn highly abstract features
among abitrary number of time related input maps ... | 0 | zrz@andrew.cmu.edu [SEP] Temporal-related Convolutional-Restricted-Boltzmann-Machine capable of learning relational order via reinforcement learning procedure? : In this article, we extend the conventional framework of
convolutional-Restricted-Boltzmann-Machine to learn highly abstract features
among abitrary number of... | 56 |
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey | Since the 2004 DARPA Grand Challenge, the autonomous driving technology has
witnessed nearly two decades of rapid development. Particularly, in recent
years, with the application of new sensors and deep learning technologies
extending to the autonomous field, the development of autonomous driving
technology has continu... | Liked | zrz@andrew.cmu.edu | Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey : Since the 2004 DARPA Grand Challenge, the autonomous driving technology has
witnessed nearly two decades of rapid development. Particularly, in recent
years, with the application of new sensors and deep learning technologies
extending ... | 1 | zrz@andrew.cmu.edu [SEP] Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey : Since the 2004 DARPA Grand Challenge, the autonomous driving technology has
witnessed nearly two decades of rapid development. Particularly, in recent
years, with the application of new sensors and deep learnin... | 223 |
UniDiffGrasp: A Unified Framework Integrating VLM Reasoning and VLM-Guided Part Diffusion for Open-Vocabulary Constrained Grasping with Dual Arms | Open-vocabulary, task-oriented grasping of specific functional parts,
particularly with dual arms, remains a key challenge, as current
Vision-Language Models (VLMs), while enhancing task understanding, often
struggle with precise grasp generation within defined constraints and effective
dual-arm coordination. We innova... | Liked | jechoi@andrew.cmu.edu | UniDiffGrasp: A Unified Framework Integrating VLM Reasoning and VLM-Guided Part Diffusion for Open-Vocabulary Constrained Grasping with Dual Arms : Open-vocabulary, task-oriented grasping of specific functional parts,
particularly with dual arms, remains a key challenge, as current
Vision-Language Models (VLMs), while ... | 1 | jechoi@andrew.cmu.edu [SEP] UniDiffGrasp: A Unified Framework Integrating VLM Reasoning and VLM-Guided Part Diffusion for Open-Vocabulary Constrained Grasping with Dual Arms : Open-vocabulary, task-oriented grasping of specific functional parts,
particularly with dual arms, remains a key challenge, as current
Vision-La... | 559 |
Design and Development of a Remotely Wire-Driven Walking Robot | Operating in environments too harsh or inaccessible for humans is one of the
critical roles expected of robots. However, such environments often pose risks
to electronic components as well. To overcome this, various approaches have
been developed, including autonomous mobile robots without electronics,
hydraulic remote... | Liked | jechoi@andrew.cmu.edu | Design and Development of a Remotely Wire-Driven Walking Robot : Operating in environments too harsh or inaccessible for humans is one of the
critical roles expected of robots. However, such environments often pose risks
to electronic components as well. To overcome this, various approaches have
been developed, includi... | 1 | jechoi@andrew.cmu.edu [SEP] Design and Development of a Remotely Wire-Driven Walking Robot : Operating in environments too harsh or inaccessible for humans is one of the
critical roles expected of robots. However, such environments often pose risks
to electronic components as well. To overcome this, various approaches ... | 19 |
Knowledge-augmented Column Networks: Guiding Deep Learning with Advice | Recently, deep models have had considerable success in several tasks,
especially with low-level representations. However, effective learning from
sparse noisy samples is a major challenge in most deep models, especially in
domains with structured representations. Inspired by the proven success of
human guided machine l... | Disliked | zrz@andrew.cmu.edu | Knowledge-augmented Column Networks: Guiding Deep Learning with Advice : Recently, deep models have had considerable success in several tasks,
especially with low-level representations. However, effective learning from
sparse noisy samples is a major challenge in most deep models, especially in
domains with structured ... | 0 | zrz@andrew.cmu.edu [SEP] Knowledge-augmented Column Networks: Guiding Deep Learning with Advice : Recently, deep models have had considerable success in several tasks,
especially with low-level representations. However, effective learning from
sparse noisy samples is a major challenge in most deep models, especially in... | 255 |
Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge | Medical vision-and-language pre-training (Med-VLP) has received considerable
attention owing to its applicability to extracting generic vision-and-language
representations from medical images and texts. Most existing methods mainly
contain three elements: uni-modal encoders (i.e., a vision encoder and a
language encode... | Liked | zrz@andrew.cmu.edu | Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge : Medical vision-and-language pre-training (Med-VLP) has received considerable
attention owing to its applicability to extracting generic vision-and-language
representations from medical images and texts. Most existing methods ma... | 1 | zrz@andrew.cmu.edu [SEP] Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge : Medical vision-and-language pre-training (Med-VLP) has received considerable
attention owing to its applicability to extracting generic vision-and-language
representations from medical images and texts.... | 349 |
Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement | We investigate the problem of coordinating two robot arms to solve
non-monotone tabletop multi-object rearrangement tasks. In a non-monotone
rearrangement task, complex object-object dependencies exist that require
moving some objects multiple times to solve an instance. In working with two
arms in a large workspace, s... | Liked | jechoi@andrew.cmu.edu | Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement : We investigate the problem of coordinating two robot arms to solve
non-monotone tabletop multi-object rearrangement tasks. In a non-monotone
rearrangement task, complex object-object dependencies exist that require
moving some objects multiple ... | 1 | jechoi@andrew.cmu.edu [SEP] Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement : We investigate the problem of coordinating two robot arms to solve
non-monotone tabletop multi-object rearrangement tasks. In a non-monotone
rearrangement task, complex object-object dependencies exist that require
m... | 21 |
Deep Learning of Representations: Looking Forward | Deep learning research aims at discovering learning algorithms that discover
multiple levels of distributed representations, with higher levels representing
more abstract concepts. Although the study of deep learning has already led to
impressive theoretical results, learning algorithms and breakthrough
experiments, se... | Liked | zrz@andrew.cmu.edu | Deep Learning of Representations: Looking Forward : Deep learning research aims at discovering learning algorithms that discover
multiple levels of distributed representations, with higher levels representing
more abstract concepts. Although the study of deep learning has already led to
impressive theoretical results, ... | 1 | zrz@andrew.cmu.edu [SEP] Deep Learning of Representations: Looking Forward : Deep learning research aims at discovering learning algorithms that discover
multiple levels of distributed representations, with higher levels representing
more abstract concepts. Although the study of deep learning has already led to
impress... | 252 |
Situation-aware Autonomous Driving Decision Making with Cooperative Perception on Demand | This paper investigates the impact of cooperative perception on autonomous
driving decision making on urban roads. The extended perception range
contributed by the cooperative perception can be properly leveraged to address
the implicit dependencies within the vehicles, thereby the vehicle decision
making performance c... | Disliked | zrz@andrew.cmu.edu | Situation-aware Autonomous Driving Decision Making with Cooperative Perception on Demand : This paper investigates the impact of cooperative perception on autonomous
driving decision making on urban roads. The extended perception range
contributed by the cooperative perception can be properly leveraged to address
the i... | 0 | zrz@andrew.cmu.edu [SEP] Situation-aware Autonomous Driving Decision Making with Cooperative Perception on Demand : This paper investigates the impact of cooperative perception on autonomous
driving decision making on urban roads. The extended perception range
contributed by the cooperative perception can be properly l... | 274 |
PSL is Dead. Long Live PSL | Property Specification Language (PSL) is a form of temporal logic that has
been mainly used in discrete domains (e.g. formal hardware verification). In
this paper, we show that by merging machine learning techniques with PSL
monitors, we can extend PSL to work on continuous domains. We apply this
technique in machine l... | Disliked | zrz@andrew.cmu.edu | PSL is Dead. Long Live PSL : Property Specification Language (PSL) is a form of temporal logic that has
been mainly used in discrete domains (e.g. formal hardware verification). In
this paper, we show that by merging machine learning techniques with PSL
monitors, we can extend PSL to work on continuous domains. We appl... | 0 | zrz@andrew.cmu.edu [SEP] PSL is Dead. Long Live PSL : Property Specification Language (PSL) is a form of temporal logic that has
been mainly used in discrete domains (e.g. formal hardware verification). In
this paper, we show that by merging machine learning techniques with PSL
monitors, we can extend PSL to work on co... | 147 |
Joint Training of Deep Boltzmann Machines | We introduce a new method for training deep Boltzmann machines jointly. Prior
methods require an initial learning pass that trains the deep Boltzmann machine
greedily, one layer at a time, or do not perform well on classifi- cation
tasks. | Disliked | zrz@andrew.cmu.edu | Joint Training of Deep Boltzmann Machines : We introduce a new method for training deep Boltzmann machines jointly. Prior
methods require an initial learning pass that trains the deep Boltzmann machine
greedily, one layer at a time, or do not perform well on classifi- cation
tasks. | 0 | zrz@andrew.cmu.edu [SEP] Joint Training of Deep Boltzmann Machines : We introduce a new method for training deep Boltzmann machines jointly. Prior
methods require an initial learning pass that trains the deep Boltzmann machine
greedily, one layer at a time, or do not perform well on classifi- cation
tasks. | 41 |
Optimal Scheduling of a Dual-Arm Robot for Efficient Strawberry Harvesting in Plant Factories | Plant factory cultivation is widely recognized for its ability to optimize
resource use and boost crop yields. To further increase the efficiency in these
environments, we propose a mixed-integer linear programming (MILP) framework
that systematically schedules and coordinates dual-arm harvesting tasks,
minimizing the ... | Liked | jechoi@andrew.cmu.edu | Optimal Scheduling of a Dual-Arm Robot for Efficient Strawberry Harvesting in Plant Factories : Plant factory cultivation is widely recognized for its ability to optimize
resource use and boost crop yields. To further increase the efficiency in these
environments, we propose a mixed-integer linear programming (MILP) fr... | 1 | jechoi@andrew.cmu.edu [SEP] Optimal Scheduling of a Dual-Arm Robot for Efficient Strawberry Harvesting in Plant Factories : Plant factory cultivation is widely recognized for its ability to optimize
resource use and boost crop yields. To further increase the efficiency in these
environments, we propose a mixed-integer ... | 476 |
Inspiring Computer Vision System Solutions | The "digital Michelangelo project" was a seminal computer vision project in
the early 2000's that pushed the capabilities of acquisition systems and
involved multiple people from diverse fields, many of whom are now leaders in
industry and academia. Reviewing this project with modern eyes provides us with
the opportuni... | Disliked | zrz@andrew.cmu.edu | Inspiring Computer Vision System Solutions : The "digital Michelangelo project" was a seminal computer vision project in
the early 2000's that pushed the capabilities of acquisition systems and
involved multiple people from diverse fields, many of whom are now leaders in
industry and academia. Reviewing this project wi... | 0 | zrz@andrew.cmu.edu [SEP] Inspiring Computer Vision System Solutions : The "digital Michelangelo project" was a seminal computer vision project in
the early 2000's that pushed the capabilities of acquisition systems and
involved multiple people from diverse fields, many of whom are now leaders in
industry and academia. ... | 355 |
Modeling Generalization in Machine Learning: A Methodological and Computational Study | As machine learning becomes more and more available to the general public,
theoretical questions are turning into pressing practical issues. Possibly, one
of the most relevant concerns is the assessment of our confidence in trusting
machine learning predictions. In many real-world cases, it is of utmost
importance to e... | Disliked | zrz@andrew.cmu.edu | Modeling Generalization in Machine Learning: A Methodological and Computational Study : As machine learning becomes more and more available to the general public,
theoretical questions are turning into pressing practical issues. Possibly, one
of the most relevant concerns is the assessment of our confidence in trusting... | 0 | zrz@andrew.cmu.edu [SEP] Modeling Generalization in Machine Learning: A Methodological and Computational Study : As machine learning becomes more and more available to the general public,
theoretical questions are turning into pressing practical issues. Possibly, one
of the most relevant concerns is the assessment of o... | 117 |
Development of a Tendon Driven Variable Stiffness Continuum Robot with Layer Jamming | The purpose of this research is to design, fabricate and test a tendon driven
a continuum soft robot with three modular segments, each of which has a tunable
stiffness enabled by layer jamming technology. Compared with previous studies,
the robotic arm design of this project has a modular structure, which means the
len... | Liked | jechoi@andrew.cmu.edu | Development of a Tendon Driven Variable Stiffness Continuum Robot with Layer Jamming : The purpose of this research is to design, fabricate and test a tendon driven
a continuum soft robot with three modular segments, each of which has a tunable
stiffness enabled by layer jamming technology. Compared with previous studi... | 1 | jechoi@andrew.cmu.edu [SEP] Development of a Tendon Driven Variable Stiffness Continuum Robot with Layer Jamming : The purpose of this research is to design, fabricate and test a tendon driven
a continuum soft robot with three modular segments, each of which has a tunable
stiffness enabled by layer jamming technology. ... | 389 |
Lecture Notes: Optimization for Machine Learning | Lecture notes on optimization for machine learning, derived from a course at
Princeton University and tutorials given in MLSS, Buenos Aires, as well as
Simons Foundation, Berkeley. | Liked | zrz@andrew.cmu.edu | Lecture Notes: Optimization for Machine Learning : Lecture notes on optimization for machine learning, derived from a course at
Princeton University and tutorials given in MLSS, Buenos Aires, as well as
Simons Foundation, Berkeley. | 1 | zrz@andrew.cmu.edu [SEP] Lecture Notes: Optimization for Machine Learning : Lecture notes on optimization for machine learning, derived from a course at
Princeton University and tutorials given in MLSS, Buenos Aires, as well as
Simons Foundation, Berkeley. | 0 |
Extremal Configuration of Robot Arms in Three Dimensions | We define a volume function for a robot arms in 3-dimensional Euclidean space
and give geometric conditions for its critical points. For 3-arms this volume
function is an exact topological Morse function on the 3-sphere. | Liked | jechoi@andrew.cmu.edu | Extremal Configuration of Robot Arms in Three Dimensions : We define a volume function for a robot arms in 3-dimensional Euclidean space
and give geometric conditions for its critical points. For 3-arms this volume
function is an exact topological Morse function on the 3-sphere. | 1 | jechoi@andrew.cmu.edu [SEP] Extremal Configuration of Robot Arms in Three Dimensions : We define a volume function for a robot arms in 3-dimensional Euclidean space
and give geometric conditions for its critical points. For 3-arms this volume
function is an exact topological Morse function on the 3-sphere. | 546 |
Fairness in Deep Learning: A Computational Perspective | Deep learning is increasingly being used in high-stake decision making
applications that affect individual lives. However, deep learning models might
exhibit algorithmic discrimination behaviors with respect to protected groups,
potentially posing negative impacts on individuals and society. Therefore,
fairness in deep... | Liked | zrz@andrew.cmu.edu | Fairness in Deep Learning: A Computational Perspective : Deep learning is increasingly being used in high-stake decision making
applications that affect individual lives. However, deep learning models might
exhibit algorithmic discrimination behaviors with respect to protected groups,
potentially posing negative impact... | 1 | zrz@andrew.cmu.edu [SEP] Fairness in Deep Learning: A Computational Perspective : Deep learning is increasingly being used in high-stake decision making
applications that affect individual lives. However, deep learning models might
exhibit algorithmic discrimination behaviors with respect to protected groups,
potential... | 224 |
Intelligent Perception System for Vehicle-Road Cooperation | With the development of autonomous driving, the improvement of autonomous
driving technology for individual vehicles has reached the bottleneck. The
advancement of vehicle-road cooperation autonomous driving technology can
expand the vehicle's perception range, supplement the perception blind area and
improve the perce... | Liked | zrz@andrew.cmu.edu | Intelligent Perception System for Vehicle-Road Cooperation : With the development of autonomous driving, the improvement of autonomous
driving technology for individual vehicles has reached the bottleneck. The
advancement of vehicle-road cooperation autonomous driving technology can
expand the vehicle's perception rang... | 1 | zrz@andrew.cmu.edu [SEP] Intelligent Perception System for Vehicle-Road Cooperation : With the development of autonomous driving, the improvement of autonomous
driving technology for individual vehicles has reached the bottleneck. The
advancement of vehicle-road cooperation autonomous driving technology can
expand the ... | 288 |
Efficient Deep Feature Learning and Extraction via StochasticNets | Deep neural networks are a powerful tool for feature learning and extraction
given their ability to model high-level abstractions in highly complex data.
One area worth exploring in feature learning and extraction using deep neural
networks is efficient neural connectivity formation for faster feature learning
and extr... | Liked | zrz@andrew.cmu.edu | Efficient Deep Feature Learning and Extraction via StochasticNets : Deep neural networks are a powerful tool for feature learning and extraction
given their ability to model high-level abstractions in highly complex data.
One area worth exploring in feature learning and extraction using deep neural
networks is efficien... | 1 | zrz@andrew.cmu.edu [SEP] Efficient Deep Feature Learning and Extraction via StochasticNets : Deep neural networks are a powerful tool for feature learning and extraction
given their ability to model high-level abstractions in highly complex data.
One area worth exploring in feature learning and extraction using deep ne... | 210 |
Theoretical Models of Learning to Learn | A Machine can only learn if it is biased in some way. Typically the bias is
supplied by hand, for example through the choice of an appropriate set of
features. However, if the learning machine is embedded within an {\em
environment} of related tasks, then it can {\em learn} its own bias by learning
sufficiently many ta... | Disliked | zrz@andrew.cmu.edu | Theoretical Models of Learning to Learn : A Machine can only learn if it is biased in some way. Typically the bias is
supplied by hand, for example through the choice of an appropriate set of
features. However, if the learning machine is embedded within an {\em
environment} of related tasks, then it can {\em learn} its... | 0 | zrz@andrew.cmu.edu [SEP] Theoretical Models of Learning to Learn : A Machine can only learn if it is biased in some way. Typically the bias is
supplied by hand, for example through the choice of an appropriate set of
features. However, if the learning machine is embedded within an {\em
environment} of related tasks, th... | 64 |
The Case for Meta-Cognitive Machine Learning: On Model Entropy and Concept Formation in Deep Learning | Machine learning is usually defined in behaviourist terms, where external
validation is the primary mechanism of learning. In this paper, I argue for a
more holistic interpretation in which finding more probable, efficient and
abstract representations is as central to learning as performance. In other
words, machine le... | Disliked | zrz@andrew.cmu.edu | The Case for Meta-Cognitive Machine Learning: On Model Entropy and Concept Formation in Deep Learning : Machine learning is usually defined in behaviourist terms, where external
validation is the primary mechanism of learning. In this paper, I argue for a
more holistic interpretation in which finding more probable, eff... | 0 | zrz@andrew.cmu.edu [SEP] The Case for Meta-Cognitive Machine Learning: On Model Entropy and Concept Formation in Deep Learning : Machine learning is usually defined in behaviourist terms, where external
validation is the primary mechanism of learning. In this paper, I argue for a
more holistic interpretation in which f... | 142 |
High-Precise Robot Arm Manipulation based on Online Iterative Learning and Forward Simulation with Positioning Error Below End-Effector Physical Minimum Displacement | Precision is a crucial performance indicator for robot arms, as high
precision manipulation allows for a wider range of applications. Traditional
methods for improving robot arm precision rely on error compensation. However,
these methods are often not robust and lack adaptability. Learning-based
methods offer greater ... | Liked | jechoi@andrew.cmu.edu | High-Precise Robot Arm Manipulation based on Online Iterative Learning and Forward Simulation with Positioning Error Below End-Effector Physical Minimum Displacement : Precision is a crucial performance indicator for robot arms, as high
precision manipulation allows for a wider range of applications. Traditional
method... | 1 | jechoi@andrew.cmu.edu [SEP] High-Precise Robot Arm Manipulation based on Online Iterative Learning and Forward Simulation with Positioning Error Below End-Effector Physical Minimum Displacement : Precision is a crucial performance indicator for robot arms, as high
precision manipulation allows for a wider range of appl... | 423 |
Mental Models of Adversarial Machine Learning | Although machine learning is widely used in practice, little is known about
practitioners' understanding of potential security challenges. In this work, we
close this substantial gap and contribute a qualitative study focusing on
developers' mental models of the machine learning pipeline and potentially
vulnerable comp... | Disliked | zrz@andrew.cmu.edu | Mental Models of Adversarial Machine Learning : Although machine learning is widely used in practice, little is known about
practitioners' understanding of potential security challenges. In this work, we
close this substantial gap and contribute a qualitative study focusing on
developers' mental models of the machine l... | 0 | zrz@andrew.cmu.edu [SEP] Mental Models of Adversarial Machine Learning : Although machine learning is widely used in practice, little is known about
practitioners' understanding of potential security challenges. In this work, we
close this substantial gap and contribute a qualitative study focusing on
developers' menta... | 111 |
Introduction to deep learning | Deep Learning (DL) has made a major impact on data science in the last
decade. This chapter introduces the basic concepts of this field. It includes
both the basic structures used to design deep neural networks and a brief
survey of some of its popular use cases. | Disliked | zrz@andrew.cmu.edu | Introduction to deep learning : Deep Learning (DL) has made a major impact on data science in the last
decade. This chapter introduces the basic concepts of this field. It includes
both the basic structures used to design deep neural networks and a brief
survey of some of its popular use cases. | 0 | zrz@andrew.cmu.edu [SEP] Introduction to deep learning : Deep Learning (DL) has made a major impact on data science in the last
decade. This chapter introduces the basic concepts of this field. It includes
both the basic structures used to design deep neural networks and a brief
survey of some of its popular use cases. | 201 |
Rethinking Causal Mask Attention for Vision-Language Inference | Causal attention has become a foundational mechanism in autoregressive
vision-language models (VLMs), unifying textual and visual inputs under a
single generative framework. However, existing causal mask-based strategies are
inherited from large language models (LLMs) where they are tailored for
text-only decoding, and... | Liked | zrz@andrew.cmu.edu | Rethinking Causal Mask Attention for Vision-Language Inference : Causal attention has become a foundational mechanism in autoregressive
vision-language models (VLMs), unifying textual and visual inputs under a
single generative framework. However, existing causal mask-based strategies are
inherited from large language ... | 1 | zrz@andrew.cmu.edu [SEP] Rethinking Causal Mask Attention for Vision-Language Inference : Causal attention has become a foundational mechanism in autoregressive
vision-language models (VLMs), unifying textual and visual inputs under a
single generative framework. However, existing causal mask-based strategies are
inher... | 379 |
Asset Pricing and Deep Learning | Traditional machine learning methods have been widely studied in financial
innovation. My study focuses on the application of deep learning methods on
asset pricing. I investigate various deep learning methods for asset pricing,
especially for risk premia measurement. All models take the same set of
predictive signals ... | Liked | zrz@andrew.cmu.edu | Asset Pricing and Deep Learning : Traditional machine learning methods have been widely studied in financial
innovation. My study focuses on the application of deep learning methods on
asset pricing. I investigate various deep learning methods for asset pricing,
especially for risk premia measurement. All models take t... | 1 | zrz@andrew.cmu.edu [SEP] Asset Pricing and Deep Learning : Traditional machine learning methods have been widely studied in financial
innovation. My study focuses on the application of deep learning methods on
asset pricing. I investigate various deep learning methods for asset pricing,
especially for risk premia measu... | 228 |
Human-vehicle Cooperative Visual Perception for Autonomous Driving under Complex Road and Traffic Scenarios | Human-vehicle cooperative driving has become the critical technology of
autonomous driving, which reduces the workload of human drivers. However, the
complex and uncertain road environments bring great challenges to the visual
perception of cooperative systems. And the perception characteristics of
autonomous driving d... | Liked | zrz@andrew.cmu.edu | Human-vehicle Cooperative Visual Perception for Autonomous Driving under Complex Road and Traffic Scenarios : Human-vehicle cooperative driving has become the critical technology of
autonomous driving, which reduces the workload of human drivers. However, the
complex and uncertain road environments bring great challeng... | 1 | zrz@andrew.cmu.edu [SEP] Human-vehicle Cooperative Visual Perception for Autonomous Driving under Complex Road and Traffic Scenarios : Human-vehicle cooperative driving has become the critical technology of
autonomous driving, which reduces the workload of human drivers. However, the
complex and uncertain road environm... | 277 |
Boosting Deep Ensembles with Learning Rate Tuning | The Learning Rate (LR) has a high impact on deep learning training
performance. A common practice is to train a Deep Neural Network (DNN) multiple
times with different LR policies to find the optimal LR policy, which has been
widely recognized as a daunting and costly task. Moreover, multiple times of
DNN training has ... | Disliked | zrz@andrew.cmu.edu | Boosting Deep Ensembles with Learning Rate Tuning : The Learning Rate (LR) has a high impact on deep learning training
performance. A common practice is to train a Deep Neural Network (DNN) multiple
times with different LR policies to find the optimal LR policy, which has been
widely recognized as a daunting and costly... | 0 | zrz@andrew.cmu.edu [SEP] Boosting Deep Ensembles with Learning Rate Tuning : The Learning Rate (LR) has a high impact on deep learning training
performance. A common practice is to train a Deep Neural Network (DNN) multiple
times with different LR policies to find the optimal LR policy, which has been
widely recognized... | 251 |
Deep Learning for Sentiment Analysis : A Survey | Deep learning has emerged as a powerful machine learning technique that
learns multiple layers of representations or features of the data and produces
state-of-the-art prediction results. Along with the success of deep learning in
many other application domains, deep learning is also popularly used in
sentiment analysi... | Liked | zrz@andrew.cmu.edu | Deep Learning for Sentiment Analysis : A Survey : Deep learning has emerged as a powerful machine learning technique that
learns multiple layers of representations or features of the data and produces
state-of-the-art prediction results. Along with the success of deep learning in
many other application domains, deep le... | 1 | zrz@andrew.cmu.edu [SEP] Deep Learning for Sentiment Analysis : A Survey : Deep learning has emerged as a powerful machine learning technique that
learns multiple layers of representations or features of the data and produces
state-of-the-art prediction results. Along with the success of deep learning in
many other app... | 181 |
Deep Neural Networks - A Brief History | Introduction to deep neural networks and their history. | Disliked | zrz@andrew.cmu.edu | Deep Neural Networks - A Brief History : Introduction to deep neural networks and their history. | 0 | zrz@andrew.cmu.edu [SEP] Deep Neural Networks - A Brief History : Introduction to deep neural networks and their history. | 353 |
Vehicle-to-Everything Cooperative Perception for Autonomous Driving | Achieving fully autonomous driving with enhanced safety and efficiency relies
on vehicle-to-everything cooperative perception, which enables vehicles to
share perception data, thereby enhancing situational awareness and overcoming
the limitations of the sensing ability of individual vehicles.
Vehicle-to-everything coop... | Liked | zrz@andrew.cmu.edu | Vehicle-to-Everything Cooperative Perception for Autonomous Driving : Achieving fully autonomous driving with enhanced safety and efficiency relies
on vehicle-to-everything cooperative perception, which enables vehicles to
share perception data, thereby enhancing situational awareness and overcoming
the limitations of ... | 1 | zrz@andrew.cmu.edu [SEP] Vehicle-to-Everything Cooperative Perception for Autonomous Driving : Achieving fully autonomous driving with enhanced safety and efficiency relies
on vehicle-to-everything cooperative perception, which enables vehicles to
share perception data, thereby enhancing situational awareness and overc... | 307 |
Proceedings of the 29th International Conference on Machine Learning (ICML-12) | This is an index to the papers that appear in the Proceedings of the 29th
International Conference on Machine Learning (ICML-12). The conference was held
in Edinburgh, Scotland, June 27th - July 3rd, 2012. | Disliked | zrz@andrew.cmu.edu | Proceedings of the 29th International Conference on Machine Learning (ICML-12) : This is an index to the papers that appear in the Proceedings of the 29th
International Conference on Machine Learning (ICML-12). The conference was held
in Edinburgh, Scotland, June 27th - July 3rd, 2012. | 0 | zrz@andrew.cmu.edu [SEP] Proceedings of the 29th International Conference on Machine Learning (ICML-12) : This is an index to the papers that appear in the Proceedings of the 29th
International Conference on Machine Learning (ICML-12). The conference was held
in Edinburgh, Scotland, June 27th - July 3rd, 2012. | 58 |
A Review of the Convergence of 5G/6G Architecture and Deep Learning | The convergence of 5G architecture and deep learning has gained a lot of
research interests in both the fields of wireless communication and artificial
intelligence. This is because deep learning technologies have been identified
to be the potential driver of the 5G technologies, that make up the 5G
architecture. Hence... | Liked | zrz@andrew.cmu.edu | A Review of the Convergence of 5G/6G Architecture and Deep Learning : The convergence of 5G architecture and deep learning has gained a lot of
research interests in both the fields of wireless communication and artificial
intelligence. This is because deep learning technologies have been identified
to be the potential ... | 1 | zrz@andrew.cmu.edu [SEP] A Review of the Convergence of 5G/6G Architecture and Deep Learning : The convergence of 5G architecture and deep learning has gained a lot of
research interests in both the fields of wireless communication and artificial
intelligence. This is because deep learning technologies have been identi... | 247 |
Bimanual crop manipulation for human-inspired robotic harvesting | Most existing robotic harvesters utilize a unimanual approach; a single arm
grasps the crop and detaches it, either via a detachment movement, or by
cutting its stem with a specially designed gripper/cutter end-effector.
However, such unimanual solutions cannot be applied for sensitive crops and
cluttered environments ... | Liked | jechoi@andrew.cmu.edu | Bimanual crop manipulation for human-inspired robotic harvesting : Most existing robotic harvesters utilize a unimanual approach; a single arm
grasps the crop and detaches it, either via a detachment movement, or by
cutting its stem with a specially designed gripper/cutter end-effector.
However, such unimanual solution... | 1 | jechoi@andrew.cmu.edu [SEP] Bimanual crop manipulation for human-inspired robotic harvesting : Most existing robotic harvesters utilize a unimanual approach; a single arm
grasps the crop and detaches it, either via a detachment movement, or by
cutting its stem with a specially designed gripper/cutter end-effector.
Howe... | 500 |
Quantum-enhanced machine learning | The emerging field of quantum machine learning has the potential to
substantially aid in the problems and scope of artificial intelligence. This is
only enhanced by recent successes in the field of classical machine learning.
In this work we propose an approach for the systematic treatment of machine
learning, from the... | Disliked | zrz@andrew.cmu.edu | Quantum-enhanced machine learning : The emerging field of quantum machine learning has the potential to
substantially aid in the problems and scope of artificial intelligence. This is
only enhanced by recent successes in the field of classical machine learning.
In this work we propose an approach for the systematic tre... | 0 | zrz@andrew.cmu.edu [SEP] Quantum-enhanced machine learning : The emerging field of quantum machine learning has the potential to
substantially aid in the problems and scope of artificial intelligence. This is
only enhanced by recent successes in the field of classical machine learning.
In this work we propose an approa... | 130 |
Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds | Autonomous vehicles may make wrong decisions due to inaccurate detection and
recognition. Therefore, an intelligent vehicle can combine its own data with
that of other vehicles to enhance perceptive ability, and thus improve
detection accuracy and driving safety. However, multi-vehicle cooperative
perception requires t... | Liked | zrz@andrew.cmu.edu | Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds : Autonomous vehicles may make wrong decisions due to inaccurate detection and
recognition. Therefore, an intelligent vehicle can combine its own data with
that of other vehicles to enhance perceptive ability, and thus improve
det... | 1 | zrz@andrew.cmu.edu [SEP] Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds : Autonomous vehicles may make wrong decisions due to inaccurate detection and
recognition. Therefore, an intelligent vehicle can combine its own data with
that of other vehicles to enhance perceptive abil... | 330 |
Engineering problems in machine learning systems | Fatal accidents are a major issue hindering the wide acceptance of
safety-critical systems that employ machine learning and deep learning models,
such as automated driving vehicles. In order to use machine learning in a
safety-critical system, it is necessary to demonstrate the safety and security
of the system through... | Liked | zrz@andrew.cmu.edu | Engineering problems in machine learning systems : Fatal accidents are a major issue hindering the wide acceptance of
safety-critical systems that employ machine learning and deep learning models,
such as automated driving vehicles. In order to use machine learning in a
safety-critical system, it is necessary to demons... | 1 | zrz@andrew.cmu.edu [SEP] Engineering problems in machine learning systems : Fatal accidents are a major issue hindering the wide acceptance of
safety-critical systems that employ machine learning and deep learning models,
such as automated driving vehicles. In order to use machine learning in a
safety-critical system, ... | 138 |
Deep Bayesian Active Learning with Image Data | Even though active learning forms an important pillar of machine learning,
deep learning tools are not prevalent within it. Deep learning poses several
difficulties when used in an active learning setting. First, active learning
(AL) methods generally rely on being able to learn and update models from small
amounts of ... | Disliked | zrz@andrew.cmu.edu | Deep Bayesian Active Learning with Image Data : Even though active learning forms an important pillar of machine learning,
deep learning tools are not prevalent within it. Deep learning poses several
difficulties when used in an active learning setting. First, active learning
(AL) methods generally rely on being able t... | 0 | zrz@andrew.cmu.edu [SEP] Deep Bayesian Active Learning with Image Data : Even though active learning forms an important pillar of machine learning,
deep learning tools are not prevalent within it. Deep learning poses several
difficulties when used in an active learning setting. First, active learning
(AL) methods gener... | 197 |
Interpretations of Deep Learning by Forests and Haar Wavelets | This paper presents a basic property of region dividing of ReLU (rectified
linear unit) deep learning when new layers are successively added, by which two
new perspectives of interpreting deep learning are given. The first is related
to decision trees and forests; we construct a deep learning structure
equivalent to a ... | Liked | zrz@andrew.cmu.edu | Interpretations of Deep Learning by Forests and Haar Wavelets : This paper presents a basic property of region dividing of ReLU (rectified
linear unit) deep learning when new layers are successively added, by which two
new perspectives of interpreting deep learning are given. The first is related
to decision trees and ... | 1 | zrz@andrew.cmu.edu [SEP] Interpretations of Deep Learning by Forests and Haar Wavelets : This paper presents a basic property of region dividing of ReLU (rectified
linear unit) deep learning when new layers are successively added, by which two
new perspectives of interpreting deep learning are given. The first is relat... | 186 |
Deep Causal Learning: Representation, Discovery and Inference | Causal learning has garnered significant attention in recent years because it
reveals the essential relationships that underpin phenomena and delineates the
mechanisms by which the world evolves. Nevertheless, traditional causal
learning methods face numerous challenges and limitations, including
high-dimensional, unst... | Liked | zrz@andrew.cmu.edu | Deep Causal Learning: Representation, Discovery and Inference : Causal learning has garnered significant attention in recent years because it
reveals the essential relationships that underpin phenomena and delineates the
mechanisms by which the world evolves. Nevertheless, traditional causal
learning methods face numer... | 1 | zrz@andrew.cmu.edu [SEP] Deep Causal Learning: Representation, Discovery and Inference : Causal learning has garnered significant attention in recent years because it
reveals the essential relationships that underpin phenomena and delineates the
mechanisms by which the world evolves. Nevertheless, traditional causal
le... | 248 |
Concept-Oriented Deep Learning | Concepts are the foundation of human deep learning, understanding, and
knowledge integration and transfer. We propose concept-oriented deep learning
(CODL) which extends (machine) deep learning with concept representations and
conceptual understanding capability. CODL addresses some of the major
limitations of deep lea... | Disliked | zrz@andrew.cmu.edu | Concept-Oriented Deep Learning : Concepts are the foundation of human deep learning, understanding, and
knowledge integration and transfer. We propose concept-oriented deep learning
(CODL) which extends (machine) deep learning with concept representations and
conceptual understanding capability. CODL addresses some of ... | 0 | zrz@andrew.cmu.edu [SEP] Concept-Oriented Deep Learning : Concepts are the foundation of human deep learning, understanding, and
knowledge integration and transfer. We propose concept-oriented deep learning
(CODL) which extends (machine) deep learning with concept representations and
conceptual understanding capability... | 159 |
An Essay on Optimization Mystery of Deep Learning | Despite the huge empirical success of deep learning, theoretical
understanding of neural networks learning process is still lacking. This is the
reason, why some of its features seem "mysterious". We emphasize two mysteries
of deep learning: generalization mystery, and optimization mystery. In this
essay we review and ... | Liked | zrz@andrew.cmu.edu | An Essay on Optimization Mystery of Deep Learning : Despite the huge empirical success of deep learning, theoretical
understanding of neural networks learning process is still lacking. This is the
reason, why some of its features seem "mysterious". We emphasize two mysteries
of deep learning: generalization mystery, an... | 1 | zrz@andrew.cmu.edu [SEP] An Essay on Optimization Mystery of Deep Learning : Despite the huge empirical success of deep learning, theoretical
understanding of neural networks learning process is still lacking. This is the
reason, why some of its features seem "mysterious". We emphasize two mysteries
of deep learning: g... | 211 |
Julia Language in Machine Learning: Algorithms, Applications, and Open Issues | Machine learning is driving development across many fields in science and
engineering. A simple and efficient programming language could accelerate
applications of machine learning in various fields. Currently, the programming
languages most commonly used to develop machine learning algorithms include
Python, MATLAB, a... | Disliked | zrz@andrew.cmu.edu | Julia Language in Machine Learning: Algorithms, Applications, and Open Issues : Machine learning is driving development across many fields in science and
engineering. A simple and efficient programming language could accelerate
applications of machine learning in various fields. Currently, the programming
languages mos... | 0 | zrz@andrew.cmu.edu [SEP] Julia Language in Machine Learning: Algorithms, Applications, and Open Issues : Machine learning is driving development across many fields in science and
engineering. A simple and efficient programming language could accelerate
applications of machine learning in various fields. Currently, the ... | 113 |
Vision Transformers in Medical Computer Vision -- A Contemplative Retrospection | Recent escalation in the field of computer vision underpins a huddle of
algorithms with the magnificent potential to unravel the information contained
within images. These computer vision algorithms are being practised in medical
image analysis and are transfiguring the perception and interpretation of
Imaging data. Am... | Liked | zrz@andrew.cmu.edu | Vision Transformers in Medical Computer Vision -- A Contemplative Retrospection : Recent escalation in the field of computer vision underpins a huddle of
algorithms with the magnificent potential to unravel the information contained
within images. These computer vision algorithms are being practised in medical
image an... | 1 | zrz@andrew.cmu.edu [SEP] Vision Transformers in Medical Computer Vision -- A Contemplative Retrospection : Recent escalation in the field of computer vision underpins a huddle of
algorithms with the magnificent potential to unravel the information contained
within images. These computer vision algorithms are being prac... | 339 |
Soft Arm-Motor Thrust Characterization for a Pneumatically Actuated Soft Morphing Quadrotor | In this work, an experimental characterization of the configuration space of
a soft, pneumatically actuated morphing quadrotor is presented, with a focus on
precise thrust characterization of its flexible arms, considering the effect of
downwash. Unlike traditional quadrotors, the soft drone has pneumatically
actuated ... | Liked | jechoi@andrew.cmu.edu | Soft Arm-Motor Thrust Characterization for a Pneumatically Actuated Soft Morphing Quadrotor : In this work, an experimental characterization of the configuration space of
a soft, pneumatically actuated morphing quadrotor is presented, with a focus on
precise thrust characterization of its flexible arms, considering the... | 1 | jechoi@andrew.cmu.edu [SEP] Soft Arm-Motor Thrust Characterization for a Pneumatically Actuated Soft Morphing Quadrotor : In this work, an experimental characterization of the configuration space of
a soft, pneumatically actuated morphing quadrotor is presented, with a focus on
precise thrust characterization of its fl... | 460 |
Towards A Rigorous Science of Interpretable Machine Learning | As machine learning systems become ubiquitous, there has been a surge of
interest in interpretable machine learning: systems that provide explanation
for their outputs. These explanations are often used to qualitatively assess
other criteria such as safety or non-discrimination. However, despite the
interest in interpr... | Disliked | zrz@andrew.cmu.edu | Towards A Rigorous Science of Interpretable Machine Learning : As machine learning systems become ubiquitous, there has been a surge of
interest in interpretable machine learning: systems that provide explanation
for their outputs. These explanations are often used to qualitatively assess
other criteria such as safety ... | 0 | zrz@andrew.cmu.edu [SEP] Towards A Rigorous Science of Interpretable Machine Learning : As machine learning systems become ubiquitous, there has been a surge of
interest in interpretable machine learning: systems that provide explanation
for their outputs. These explanations are often used to qualitatively assess
other... | 71 |
Transfer Learning for Voice Activity Detection: A Denoising Deep Neural Network Perspective | Mismatching problem between the source and target noisy corpora severely
hinder the practical use of the machine-learning-based voice activity detection
(VAD). In this paper, we try to address this problem in the transfer learning
prospective. Transfer learning tries to find a common learning machine or a
common featur... | Disliked | zrz@andrew.cmu.edu | Transfer Learning for Voice Activity Detection: A Denoising Deep Neural Network Perspective : Mismatching problem between the source and target noisy corpora severely
hinder the practical use of the machine-learning-based voice activity detection
(VAD). In this paper, we try to address this problem in the transfer lear... | 0 | zrz@andrew.cmu.edu [SEP] Transfer Learning for Voice Activity Detection: A Denoising Deep Neural Network Perspective : Mismatching problem between the source and target noisy corpora severely
hinder the practical use of the machine-learning-based voice activity detection
(VAD). In this paper, we try to address this pro... | 149 |
Scientific Exploration of Challenging Planetary Analog Environments with a Team of Legged Robots | The interest in exploring planetary bodies for scientific investigation and
in-situ resource utilization is ever-rising. Yet, many sites of interest are
inaccessible to state-of-the-art planetary exploration robots because of the
robots' inability to traverse steep slopes, unstructured terrain, and loose
soil. Addition... | Disliked | jechoi@andrew.cmu.edu | Scientific Exploration of Challenging Planetary Analog Environments with a Team of Legged Robots : The interest in exploring planetary bodies for scientific investigation and
in-situ resource utilization is ever-rising. Yet, many sites of interest are
inaccessible to state-of-the-art planetary exploration robots becaus... | 0 | jechoi@andrew.cmu.edu [SEP] Scientific Exploration of Challenging Planetary Analog Environments with a Team of Legged Robots : The interest in exploring planetary bodies for scientific investigation and
in-situ resource utilization is ever-rising. Yet, many sites of interest are
inaccessible to state-of-the-art planeta... | 548 |
PAPRAS: Plug-And-Play Robotic Arm System | This paper presents a novel robotic arm system, named PAPRAS (Plug-And-Play
Robotic Arm System). PAPRAS consists of a portable robotic arm(s), docking
mount(s), and software architecture including a control system. By analyzing
the target task spaces at home, the dimensions and configuration of PAPRAS are
determined. P... | Liked | jechoi@andrew.cmu.edu | PAPRAS: Plug-And-Play Robotic Arm System : This paper presents a novel robotic arm system, named PAPRAS (Plug-And-Play
Robotic Arm System). PAPRAS consists of a portable robotic arm(s), docking
mount(s), and software architecture including a control system. By analyzing
the target task spaces at home, the dimensions an... | 1 | jechoi@andrew.cmu.edu [SEP] PAPRAS: Plug-And-Play Robotic Arm System : This paper presents a novel robotic arm system, named PAPRAS (Plug-And-Play
Robotic Arm System). PAPRAS consists of a portable robotic arm(s), docking
mount(s), and software architecture including a control system. By analyzing
the target task space... | 457 |
The configuration space of a robotic arm in a tunnel | We study the motion of a robotic arm inside a rectangular tunnel. We prove
that the configuration space of all possible positions of the robot is a CAT(0)
cubical complex. This allows us to use techniques from geometric group theory
to find the optimal way of moving the arm from one position to another. We also
compute... | Liked | jechoi@andrew.cmu.edu | The configuration space of a robotic arm in a tunnel : We study the motion of a robotic arm inside a rectangular tunnel. We prove
that the configuration space of all possible positions of the robot is a CAT(0)
cubical complex. This allows us to use techniques from geometric group theory
to find the optimal way of movin... | 1 | jechoi@andrew.cmu.edu [SEP] The configuration space of a robotic arm in a tunnel : We study the motion of a robotic arm inside a rectangular tunnel. We prove
that the configuration space of all possible positions of the robot is a CAT(0)
cubical complex. This allows us to use techniques from geometric group theory
to f... | 472 |
An Anomaly Behavior Analysis Framework for Securing Autonomous Vehicle Perception | As a rapidly growing cyber-physical platform, Autonomous Vehicles (AVs) are
encountering more security challenges as their capabilities continue to expand.
In recent years, adversaries are actively targeting the perception sensors of
autonomous vehicles with sophisticated attacks that are not easily detected by
the veh... | Disliked | zrz@andrew.cmu.edu | An Anomaly Behavior Analysis Framework for Securing Autonomous Vehicle Perception : As a rapidly growing cyber-physical platform, Autonomous Vehicles (AVs) are
encountering more security challenges as their capabilities continue to expand.
In recent years, adversaries are actively targeting the perception sensors of
au... | 0 | zrz@andrew.cmu.edu [SEP] An Anomaly Behavior Analysis Framework for Securing Autonomous Vehicle Perception : As a rapidly growing cyber-physical platform, Autonomous Vehicles (AVs) are
encountering more security challenges as their capabilities continue to expand.
In recent years, adversaries are actively targeting the... | 305 |
Continuous Collision Detection for a Robotic Arm Mounted on a Cable-Driven Parallel Robot | A continuous collision checking method for a cable-driven parallel robot with
an embarked robotic arm is proposed in this paper. The method aims at
validating paths by checking for collisions between any pair of robot bodies
(mobile platform, cables, and arm links). For a pair of bodies, an upper bound
on their relativ... | Liked | jechoi@andrew.cmu.edu | Continuous Collision Detection for a Robotic Arm Mounted on a Cable-Driven Parallel Robot : A continuous collision checking method for a cable-driven parallel robot with
an embarked robotic arm is proposed in this paper. The method aims at
validating paths by checking for collisions between any pair of robot bodies
(mo... | 1 | jechoi@andrew.cmu.edu [SEP] Continuous Collision Detection for a Robotic Arm Mounted on a Cable-Driven Parallel Robot : A continuous collision checking method for a cable-driven parallel robot with
an embarked robotic arm is proposed in this paper. The method aims at
validating paths by checking for collisions between ... | 528 |
Components of Machine Learning: Binding Bits and FLOPS | Many machine learning problems and methods are combinations of three
components: data, hypothesis space and loss function. Different machine
learning methods are obtained as combinations of different choices for the
representation of data, hypothesis space and loss function. After reviewing the
mathematical structure o... | Disliked | zrz@andrew.cmu.edu | Components of Machine Learning: Binding Bits and FLOPS : Many machine learning problems and methods are combinations of three
components: data, hypothesis space and loss function. Different machine
learning methods are obtained as combinations of different choices for the
representation of data, hypothesis space and lo... | 0 | zrz@andrew.cmu.edu [SEP] Components of Machine Learning: Binding Bits and FLOPS : Many machine learning problems and methods are combinations of three
components: data, hypothesis space and loss function. Different machine
learning methods are obtained as combinations of different choices for the
representation of data... | 59 |
Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation | Embodied interaction has been introduced to human-robot interaction (HRI) as
a type of teleoperation, in which users control robot arms with bodily action
via handheld controllers or haptic gloves. Embodied teleoperation has made
robot control intuitive to non-technical users, but differences between humans'
and robots... | Liked | jechoi@andrew.cmu.edu | Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation : Embodied interaction has been introduced to human-robot interaction (HRI) as
a type of teleoperation, in which users control robot arms with bodily action
via handheld controllers or haptic gloves. Embodied teleoperation ha... | 1 | jechoi@andrew.cmu.edu [SEP] Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation : Embodied interaction has been introduced to human-robot interaction (HRI) as
a type of teleoperation, in which users control robot arms with bodily action
via handheld controllers or haptic glove... | 386 |
Stochastic Variational Deep Kernel Learning | Deep kernel learning combines the non-parametric flexibility of kernel
methods with the inductive biases of deep learning architectures. We propose a
novel deep kernel learning model and stochastic variational inference procedure
which generalizes deep kernel learning approaches to enable classification,
multi-task lea... | Disliked | zrz@andrew.cmu.edu | Stochastic Variational Deep Kernel Learning : Deep kernel learning combines the non-parametric flexibility of kernel
methods with the inductive biases of deep learning architectures. We propose a
novel deep kernel learning model and stochastic variational inference procedure
which generalizes deep kernel learning appro... | 0 | zrz@andrew.cmu.edu [SEP] Stochastic Variational Deep Kernel Learning : Deep kernel learning combines the non-parametric flexibility of kernel
methods with the inductive biases of deep learning architectures. We propose a
novel deep kernel learning model and stochastic variational inference procedure
which generalizes d... | 245 |
Towards Modular Machine Learning Solution Development: Benefits and Trade-offs | Machine learning technologies have demonstrated immense capabilities in
various domains. They play a key role in the success of modern businesses.
However, adoption of machine learning technologies has a lot of untouched
potential. Cost of developing custom machine learning solutions that solve
unique business problems... | Liked | zrz@andrew.cmu.edu | Towards Modular Machine Learning Solution Development: Benefits and Trade-offs : Machine learning technologies have demonstrated immense capabilities in
various domains. They play a key role in the success of modern businesses.
However, adoption of machine learning technologies has a lot of untouched
potential. Cost of... | 1 | zrz@andrew.cmu.edu [SEP] Towards Modular Machine Learning Solution Development: Benefits and Trade-offs : Machine learning technologies have demonstrated immense capabilities in
various domains. They play a key role in the success of modern businesses.
However, adoption of machine learning technologies has a lot of unt... | 25 |
Minimax deviation strategies for machine learning and recognition with short learning samples | The article is devoted to the problem of small learning samples in machine
learning. The flaws of maximum likelihood learning and minimax learning are
looked into and the concept of minimax deviation learning is introduced that is
free of those flaws. | Liked | zrz@andrew.cmu.edu | Minimax deviation strategies for machine learning and recognition with short learning samples : The article is devoted to the problem of small learning samples in machine
learning. The flaws of maximum likelihood learning and minimax learning are
looked into and the concept of minimax deviation learning is introduced t... | 1 | zrz@andrew.cmu.edu [SEP] Minimax deviation strategies for machine learning and recognition with short learning samples : The article is devoted to the problem of small learning samples in machine
learning. The flaws of maximum likelihood learning and minimax learning are
looked into and the concept of minimax deviation... | 1 |
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... | 403 |
Design and Development of a Remotely Wire-Driven Walking Robot | Operating in environments too harsh or inaccessible for humans is one of the
critical roles expected of robots. However, such environments often pose risks
to electronic components as well. To overcome this, various approaches have
been developed, including autonomous mobile robots without electronics,
hydraulic remote... | Disliked | jechoi@andrew.cmu.edu | Design and Development of a Remotely Wire-Driven Walking Robot : Operating in environments too harsh or inaccessible for humans is one of the
critical roles expected of robots. However, such environments often pose risks
to electronic components as well. To overcome this, various approaches have
been developed, includi... | 0 | jechoi@andrew.cmu.edu [SEP] Design and Development of a Remotely Wire-Driven Walking Robot : Operating in environments too harsh or inaccessible for humans is one of the
critical roles expected of robots. However, such environments often pose risks
to electronic components as well. To overcome this, various approaches ... | 401 |
Wheeled Humanoid Bilateral Teleoperation with Position-Force Control Modes for Dynamic Loco-Manipulation | Remote-controlled humanoid robots can revolutionize manufacturing,
construction, and healthcare industries by performing complex or dangerous
manual tasks traditionally done by humans. We refer to these behaviors as
Dynamic Loco-Manipulation (DLM). To successfully complete these tasks, humans
control the position of th... | Liked | jechoi@andrew.cmu.edu | Wheeled Humanoid Bilateral Teleoperation with Position-Force Control Modes for Dynamic Loco-Manipulation : Remote-controlled humanoid robots can revolutionize manufacturing,
construction, and healthcare industries by performing complex or dangerous
manual tasks traditionally done by humans. We refer to these behaviors ... | 1 | jechoi@andrew.cmu.edu [SEP] Wheeled Humanoid Bilateral Teleoperation with Position-Force Control Modes for Dynamic Loco-Manipulation : Remote-controlled humanoid robots can revolutionize manufacturing,
construction, and healthcare industries by performing complex or dangerous
manual tasks traditionally done by humans. ... | 563 |
Meaningful Models: Utilizing Conceptual Structure to Improve Machine Learning Interpretability | The last decade has seen huge progress in the development of advanced machine
learning models; however, those models are powerless unless human users can
interpret them. Here we show how the mind's construction of concepts and
meaning can be used to create more interpretable machine learning models. By
proposing a nove... | Disliked | zrz@andrew.cmu.edu | Meaningful Models: Utilizing Conceptual Structure to Improve Machine Learning Interpretability : The last decade has seen huge progress in the development of advanced machine
learning models; however, those models are powerless unless human users can
interpret them. Here we show how the mind's construction of concepts ... | 0 | zrz@andrew.cmu.edu [SEP] Meaningful Models: Utilizing Conceptual Structure to Improve Machine Learning Interpretability : The last decade has seen huge progress in the development of advanced machine
learning models; however, those models are powerless unless human users can
interpret them. Here we show how the mind's ... | 154 |
Configuration Tracking Control of a Multi-Segment Soft Robotic Arm Using a Cosserat Rod Model | Controlling soft continuum robotic arms is challenging due to their
hyper-redundancy and dexterity. In this paper we demonstrate, for the first
time, closed-loop control of the configuration space variables of a soft
robotic arm, composed of independently controllable segments, using a Cosserat
rod model of the robot a... | Liked | jechoi@andrew.cmu.edu | Configuration Tracking Control of a Multi-Segment Soft Robotic Arm Using a Cosserat Rod Model : Controlling soft continuum robotic arms is challenging due to their
hyper-redundancy and dexterity. In this paper we demonstrate, for the first
time, closed-loop control of the configuration space variables of a soft
robotic... | 1 | jechoi@andrew.cmu.edu [SEP] Configuration Tracking Control of a Multi-Segment Soft Robotic Arm Using a Cosserat Rod Model : Controlling soft continuum robotic arms is challenging due to their
hyper-redundancy and dexterity. In this paper we demonstrate, for the first
time, closed-loop control of the configuration space... | 447 |
Robustness Evaluation of Machine Learning Models for Robot Arm Action Recognition in Noisy Environments | In the realm of robot action recognition, identifying distinct but spatially
proximate arm movements using vision systems in noisy environments poses a
significant challenge. This paper studies robot arm action recognition in noisy
environments using machine learning techniques. Specifically, a vision system
is used to... | Liked | jechoi@andrew.cmu.edu | Robustness Evaluation of Machine Learning Models for Robot Arm Action Recognition in Noisy Environments : In the realm of robot action recognition, identifying distinct but spatially
proximate arm movements using vision systems in noisy environments poses a
significant challenge. This paper studies robot arm action rec... | 1 | jechoi@andrew.cmu.edu [SEP] Robustness Evaluation of Machine Learning Models for Robot Arm Action Recognition in Noisy Environments : In the realm of robot action recognition, identifying distinct but spatially
proximate arm movements using vision systems in noisy environments poses a
significant challenge. This paper ... | 501 |
Generalization and Expressivity for Deep Nets | Along with the rapid development of deep learning in practice, the
theoretical explanations for its success become urgent. Generalization and
expressivity are two widely used measurements to quantify theoretical behaviors
of deep learning. The expressivity focuses on finding functions expressible by
deep nets but canno... | Liked | zrz@andrew.cmu.edu | Generalization and Expressivity for Deep Nets : Along with the rapid development of deep learning in practice, the
theoretical explanations for its success become urgent. Generalization and
expressivity are two widely used measurements to quantify theoretical behaviors
of deep learning. The expressivity focuses on find... | 1 | zrz@andrew.cmu.edu [SEP] Generalization and Expressivity for Deep Nets : Along with the rapid development of deep learning in practice, the
theoretical explanations for its success become urgent. Generalization and
expressivity are two widely used measurements to quantify theoretical behaviors
of deep learning. The exp... | 190 |
Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training | The foundation models based on pre-training technology have significantly
advanced artificial intelligence from theoretical to practical applications.
These models have facilitated the feasibility of computer-aided diagnosis for
widespread use. Medical contrastive vision-language pre-training, which does
not require hu... | Liked | zrz@andrew.cmu.edu | Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training : The foundation models based on pre-training technology have significantly
advanced artificial intelligence from theoretical to practical applications.
These models have facilitated the feasibility of computer-aided diagnosis for
widesprea... | 1 | zrz@andrew.cmu.edu [SEP] Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training : The foundation models based on pre-training technology have significantly
advanced artificial intelligence from theoretical to practical applications.
These models have facilitated the feasibility of computer-aide... | 356 |
Deep Learning vs. Traditional Computer Vision | Deep Learning has pushed the limits of what was possible in the domain of
Digital Image Processing. However, that is not to say that the traditional
computer vision techniques which had been undergoing progressive development in
years prior to the rise of DL have become obsolete. This paper will analyse the
benefits an... | Disliked | zrz@andrew.cmu.edu | Deep Learning vs. Traditional Computer Vision : Deep Learning has pushed the limits of what was possible in the domain of
Digital Image Processing. However, that is not to say that the traditional
computer vision techniques which had been undergoing progressive development in
years prior to the rise of DL have become o... | 0 | zrz@andrew.cmu.edu [SEP] Deep Learning vs. Traditional Computer Vision : Deep Learning has pushed the limits of what was possible in the domain of
Digital Image Processing. However, that is not to say that the traditional
computer vision techniques which had been undergoing progressive development in
years prior to the... | 342 |
Dynamic V2X Autonomous Perception from Road-to-Vehicle Vision | Vehicle-to-everything (V2X) perception is an innovative technology that
enhances vehicle perception accuracy, thereby elevating the security and
reliability of autonomous systems. However, existing V2X perception methods
focus on static scenes from mainly vehicle-based vision, which is constrained
by sensor capabilitie... | Disliked | zrz@andrew.cmu.edu | Dynamic V2X Autonomous Perception from Road-to-Vehicle Vision : Vehicle-to-everything (V2X) perception is an innovative technology that
enhances vehicle perception accuracy, thereby elevating the security and
reliability of autonomous systems. However, existing V2X perception methods
focus on static scenes from mainly ... | 0 | zrz@andrew.cmu.edu [SEP] Dynamic V2X Autonomous Perception from Road-to-Vehicle Vision : Vehicle-to-everything (V2X) perception is an innovative technology that
enhances vehicle perception accuracy, thereby elevating the security and
reliability of autonomous systems. However, existing V2X perception methods
focus on s... | 287 |
Real-life Implementation of Internet of Robotic Things Using 5 DoF Heterogeneous Robotic Arm | Establishing a communication bridge by transferring data driven from
different embedded sensors via internet or reconcilable network protocols
between enormous number of distinctively addressable objects or "things", is
known as the Internet of Things (IoT). IoT can be amalgamated with
multitudinous objects such as the... | Liked | jechoi@andrew.cmu.edu | Real-life Implementation of Internet of Robotic Things Using 5 DoF Heterogeneous Robotic Arm : Establishing a communication bridge by transferring data driven from
different embedded sensors via internet or reconcilable network protocols
between enormous number of distinctively addressable objects or "things", is
known... | 1 | jechoi@andrew.cmu.edu [SEP] Real-life Implementation of Internet of Robotic Things Using 5 DoF Heterogeneous Robotic Arm : Establishing a communication bridge by transferring data driven from
different embedded sensors via internet or reconcilable network protocols
between enormous number of distinctively addressable o... | 417 |
Optimal path planning and weighted control of a four-arm robot in on-orbit servicing | This paper presents a trajectory optimization and control approach for the
guidance of an orbital four-arm robot in extravehicular activities. The robot
operates near the target spacecraft, enabling its arm's end-effectors to reach
the spacecraft's surface. Connections to the target spacecraft can be
established by the... | Liked | jechoi@andrew.cmu.edu | Optimal path planning and weighted control of a four-arm robot in on-orbit servicing : This paper presents a trajectory optimization and control approach for the
guidance of an orbital four-arm robot in extravehicular activities. The robot
operates near the target spacecraft, enabling its arm's end-effectors to reach
t... | 1 | jechoi@andrew.cmu.edu [SEP] Optimal path planning and weighted control of a four-arm robot in on-orbit servicing : This paper presents a trajectory optimization and control approach for the
guidance of an orbital four-arm robot in extravehicular activities. The robot
operates near the target spacecraft, enabling its ar... | 502 |
Plant-inspired behavior-based controller to enable reaching in redundant continuum robot arms | Enabling reaching capabilities in highly redundant continuum robot arms is an
active area of research. Existing solutions comprise of task-space controllers,
whose proper functioning is still limited to laboratory environments. In
contrast, this work proposes a novel plant-inspired behaviour-based controller
that explo... | Liked | jechoi@andrew.cmu.edu | Plant-inspired behavior-based controller to enable reaching in redundant continuum robot arms : Enabling reaching capabilities in highly redundant continuum robot arms is an
active area of research. Existing solutions comprise of task-space controllers,
whose proper functioning is still limited to laboratory environmen... | 1 | jechoi@andrew.cmu.edu [SEP] Plant-inspired behavior-based controller to enable reaching in redundant continuum robot arms : Enabling reaching capabilities in highly redundant continuum robot arms is an
active area of research. Existing solutions comprise of task-space controllers,
whose proper functioning is still limi... | 515 |
A Theory of Machine Learning | We critically review three major theories of machine learning and provide a
new theory according to which machines learn a function when the machines
successfully compute it. We show that this theory challenges common assumptions
in the statistical and the computational learning theories, for it implies that
learning t... | Liked | zrz@andrew.cmu.edu | A Theory of Machine Learning : We critically review three major theories of machine learning and provide a
new theory according to which machines learn a function when the machines
successfully compute it. We show that this theory challenges common assumptions
in the statistical and the computational learning theories,... | 1 | zrz@andrew.cmu.edu [SEP] A Theory of Machine Learning : We critically review three major theories of machine learning and provide a
new theory according to which machines learn a function when the machines
successfully compute it. We show that this theory challenges common assumptions
in the statistical and the computa... | 103 |
Towards Modular Machine Learning Solution Development: Benefits and Trade-offs | Machine learning technologies have demonstrated immense capabilities in
various domains. They play a key role in the success of modern businesses.
However, adoption of machine learning technologies has a lot of untouched
potential. Cost of developing custom machine learning solutions that solve
unique business problems... | Disliked | zrz@andrew.cmu.edu | Towards Modular Machine Learning Solution Development: Benefits and Trade-offs : Machine learning technologies have demonstrated immense capabilities in
various domains. They play a key role in the success of modern businesses.
However, adoption of machine learning technologies has a lot of untouched
potential. Cost of... | 0 | zrz@andrew.cmu.edu [SEP] Towards Modular Machine Learning Solution Development: Benefits and Trade-offs : Machine learning technologies have demonstrated immense capabilities in
various domains. They play a key role in the success of modern businesses.
However, adoption of machine learning technologies has a lot of unt... | 5 |
Computer Vision for Autonomous Vehicles | In this work, we try to implement Image Processing techniques in the area of
autonomous vehicles, both indoor and outdoor. The challenges for both are
different and the ways to tackle them vary too. We also showed deep learning
makes things easier and precise. We also made base models for all the problems
we tackle whi... | Liked | zrz@andrew.cmu.edu | Computer Vision for Autonomous Vehicles : In this work, we try to implement Image Processing techniques in the area of
autonomous vehicles, both indoor and outdoor. The challenges for both are
different and the ways to tackle them vary too. We also showed deep learning
makes things easier and precise. We also made base... | 1 | zrz@andrew.cmu.edu [SEP] Computer Vision for Autonomous Vehicles : In this work, we try to implement Image Processing techniques in the area of
autonomous vehicles, both indoor and outdoor. The challenges for both are
different and the ways to tackle them vary too. We also showed deep learning
makes things easier and p... | 350 |
Is 'Unsupervised Learning' a Misconceived Term? | Is all of machine learning supervised to some degree? The field of machine
learning has traditionally been categorized pedagogically into
$supervised~vs~unsupervised~learning$; where supervised learning has typically
referred to learning from labeled data, while unsupervised learning has
typically referred to learning ... | Liked | zrz@andrew.cmu.edu | Is 'Unsupervised Learning' a Misconceived Term? : Is all of machine learning supervised to some degree? The field of machine
learning has traditionally been categorized pedagogically into
$supervised~vs~unsupervised~learning$; where supervised learning has typically
referred to learning from labeled data, while unsuper... | 1 | zrz@andrew.cmu.edu [SEP] Is 'Unsupervised Learning' a Misconceived Term? : Is all of machine learning supervised to some degree? The field of machine
learning has traditionally been categorized pedagogically into
$supervised~vs~unsupervised~learning$; where supervised learning has typically
referred to learning from la... | 133 |
How Artists Improvise and Provoke Robotics | We explore transdisciplinary collaborations between artists and roboticists
across a portfolio of artworks. Brendan Walker's Broncomatic was a breath
controlled mechanical rodeo bull ride. Blast Theory's Cat Royale deployed a
robot arm to play with a family of three cats for twelve days. Different Bodies
is a prototype... | Disliked | jechoi@andrew.cmu.edu | How Artists Improvise and Provoke Robotics : We explore transdisciplinary collaborations between artists and roboticists
across a portfolio of artworks. Brendan Walker's Broncomatic was a breath
controlled mechanical rodeo bull ride. Blast Theory's Cat Royale deployed a
robot arm to play with a family of three cats for... | 0 | jechoi@andrew.cmu.edu [SEP] How Artists Improvise and Provoke Robotics : We explore transdisciplinary collaborations between artists and roboticists
across a portfolio of artworks. Brendan Walker's Broncomatic was a breath
controlled mechanical rodeo bull ride. Blast Theory's Cat Royale deployed a
robot arm to play wit... | 567 |
A Classification of Configuration Spaces of Planar Robot Arms with Application to a Continuous Inverse Kinematics Problem | Using results on the topology of moduli space of polygons [Jaggi, 92;
Kapovich and Millson, 94], it can be shown that for a planar robot arm with $n$
segments there are some values of the base-length, $z$, at which the
configuration space of the constrained arm (arm with its end effector fixed)
has two disconnected com... | Liked | jechoi@andrew.cmu.edu | A Classification of Configuration Spaces of Planar Robot Arms with Application to a Continuous Inverse Kinematics Problem : Using results on the topology of moduli space of polygons [Jaggi, 92;
Kapovich and Millson, 94], it can be shown that for a planar robot arm with $n$
segments there are some values of the base-len... | 1 | jechoi@andrew.cmu.edu [SEP] A Classification of Configuration Spaces of Planar Robot Arms with Application to a Continuous Inverse Kinematics Problem : Using results on the topology of moduli space of polygons [Jaggi, 92;
Kapovich and Millson, 94], it can be shown that for a planar robot arm with $n$
segments there are... | 504 |
Dynamic Parameter Identification of a Curtain Wall Installation Robotic Arm | In the construction industry, traditional methods fail to meet the modern
demands for efficiency and quality. The curtain wall installation is a critical
component of construction projects. We design a hydraulically driven robotic
arm for curtain wall installation and a dynamic parameter identification
method. We estab... | Liked | jechoi@andrew.cmu.edu | Dynamic Parameter Identification of a Curtain Wall Installation Robotic Arm : In the construction industry, traditional methods fail to meet the modern
demands for efficiency and quality. The curtain wall installation is a critical
component of construction projects. We design a hydraulically driven robotic
arm for cur... | 1 | jechoi@andrew.cmu.edu [SEP] Dynamic Parameter Identification of a Curtain Wall Installation Robotic Arm : In the construction industry, traditional methods fail to meet the modern
demands for efficiency and quality. The curtain wall installation is a critical
component of construction projects. We design a hydraulicall... | 456 |
Modeling and Control of an Omnidirectional Micro Aerial Vehicle Equipped with a Soft Robotic Arm | Flying manipulators are aerial drones with attached rigid-bodied robotic arms
and belong to the latest and most actively developed research areas in
robotics. The rigid nature of these arms often lack compliance, flexibility,
and smoothness in movement. This work proposes to use a soft-bodied robotic arm
attached to an... | Liked | jechoi@andrew.cmu.edu | Modeling and Control of an Omnidirectional Micro Aerial Vehicle Equipped with a Soft Robotic Arm : Flying manipulators are aerial drones with attached rigid-bodied robotic arms
and belong to the latest and most actively developed research areas in
robotics. The rigid nature of these arms often lack compliance, flexibil... | 1 | jechoi@andrew.cmu.edu [SEP] Modeling and Control of an Omnidirectional Micro Aerial Vehicle Equipped with a Soft Robotic Arm : Flying manipulators are aerial drones with attached rigid-bodied robotic arms
and belong to the latest and most actively developed research areas in
robotics. The rigid nature of these arms oft... | 508 |
metric-learn: Metric Learning Algorithms in Python | metric-learn is an open source Python package implementing supervised and
weakly-supervised distance metric learning algorithms. As part of
scikit-learn-contrib, it provides a unified interface compatible with
scikit-learn which allows to easily perform cross-validation, model selection,
and pipelining with other machi... | Liked | zrz@andrew.cmu.edu | metric-learn: Metric Learning Algorithms in Python : metric-learn is an open source Python package implementing supervised and
weakly-supervised distance metric learning algorithms. As part of
scikit-learn-contrib, it provides a unified interface compatible with
scikit-learn which allows to easily perform cross-validat... | 1 | zrz@andrew.cmu.edu [SEP] metric-learn: Metric Learning Algorithms in Python : metric-learn is an open source Python package implementing supervised and
weakly-supervised distance metric learning algorithms. As part of
scikit-learn-contrib, it provides a unified interface compatible with
scikit-learn which allows to eas... | 60 |
U2UData: A Large-scale Cooperative Perception Dataset for Swarm UAVs Autonomous Flight | Modern perception systems for autonomous flight are sensitive to occlusion
and have limited long-range capability, which is a key bottleneck in improving
low-altitude economic task performance. Recent research has shown that the
UAV-to-UAV (U2U) cooperative perception system has great potential to
revolutionize the aut... | Disliked | zrz@andrew.cmu.edu | U2UData: A Large-scale Cooperative Perception Dataset for Swarm UAVs Autonomous Flight : Modern perception systems for autonomous flight are sensitive to occlusion
and have limited long-range capability, which is a key bottleneck in improving
low-altitude economic task performance. Recent research has shown that the
UA... | 0 | zrz@andrew.cmu.edu [SEP] U2UData: A Large-scale Cooperative Perception Dataset for Swarm UAVs Autonomous Flight : Modern perception systems for autonomous flight are sensitive to occlusion
and have limited long-range capability, which is a key bottleneck in improving
low-altitude economic task performance. Recent resea... | 316 |
Challenges and Opportunities in Quantum Machine Learning | At the intersection of machine learning and quantum computing, Quantum
Machine Learning (QML) has the potential of accelerating data analysis,
especially for quantum data, with applications for quantum materials,
biochemistry, and high-energy physics. Nevertheless, challenges remain
regarding the trainability of QML mo... | Disliked | zrz@andrew.cmu.edu | Challenges and Opportunities in Quantum Machine Learning : At the intersection of machine learning and quantum computing, Quantum
Machine Learning (QML) has the potential of accelerating data analysis,
especially for quantum data, with applications for quantum materials,
biochemistry, and high-energy physics. Neverthel... | 0 | zrz@andrew.cmu.edu [SEP] Challenges and Opportunities in Quantum Machine Learning : At the intersection of machine learning and quantum computing, Quantum
Machine Learning (QML) has the potential of accelerating data analysis,
especially for quantum data, with applications for quantum materials,
biochemistry, and high-... | 107 |
Deep reinforcement learning for optical systems: A case study of mode-locked lasers | We demonstrate that deep reinforcement learning (deep RL) provides a highly
effective strategy for the control and self-tuning of optical systems. Deep RL
integrates the two leading machine learning architectures of deep neural
networks and reinforcement learning to produce robust and stable learning for
control. Deep ... | Disliked | zrz@andrew.cmu.edu | Deep reinforcement learning for optical systems: A case study of mode-locked lasers : We demonstrate that deep reinforcement learning (deep RL) provides a highly
effective strategy for the control and self-tuning of optical systems. Deep RL
integrates the two leading machine learning architectures of deep neural
networ... | 0 | zrz@andrew.cmu.edu [SEP] Deep reinforcement learning for optical systems: A case study of mode-locked lasers : We demonstrate that deep reinforcement learning (deep RL) provides a highly
effective strategy for the control and self-tuning of optical systems. Deep RL
integrates the two leading machine learning architectu... | 196 |
Design and Engineering of a Chess-Robotic Arm | In the scope of the "Chess-Bot" project, this study's goal is to choose the
right model for the robotic arm that the "the Chess-Bot" will use to move the
pawn from a cell to another. In this paper, there is the definition and the
structure of a robot arm. Also, the different engineering and kinematics
fundamentals of t... | Disliked | jechoi@andrew.cmu.edu | Design and Engineering of a Chess-Robotic Arm : In the scope of the "Chess-Bot" project, this study's goal is to choose the
right model for the robotic arm that the "the Chess-Bot" will use to move the
pawn from a cell to another. In this paper, there is the definition and the
structure of a robot arm. Also, the differ... | 0 | jechoi@andrew.cmu.edu [SEP] Design and Engineering of a Chess-Robotic Arm : In the scope of the "Chess-Bot" project, this study's goal is to choose the
right model for the robotic arm that the "the Chess-Bot" will use to move the
pawn from a cell to another. In this paper, there is the definition and the
structure of a... | 17 |
Proceedings of the 2016 ICML Workshop on #Data4Good: Machine Learning in Social Good Applications | This is the Proceedings of the ICML Workshop on #Data4Good: Machine Learning
in Social Good Applications, which was held on June 24, 2016 in New York. | Disliked | zrz@andrew.cmu.edu | Proceedings of the 2016 ICML Workshop on #Data4Good: Machine Learning in Social Good Applications : This is the Proceedings of the ICML Workshop on #Data4Good: Machine Learning
in Social Good Applications, which was held on June 24, 2016 in New York. | 0 | zrz@andrew.cmu.edu [SEP] Proceedings of the 2016 ICML Workshop on #Data4Good: Machine Learning in Social Good Applications : This is the Proceedings of the ICML Workshop on #Data4Good: Machine Learning
in Social Good Applications, which was held on June 24, 2016 in New York. | 44 |
Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle | Deep Learning has enabled many advances in machine learning applications in
the last few years. However, since current Deep Learning algorithms require
much energy for computations, there are growing concerns about the associated
environmental costs. Energy-efficient Deep Learning has received much attention
from resea... | Disliked | zrz@andrew.cmu.edu | Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle : Deep Learning has enabled many advances in machine learning applications in
the last few years. However, since current Deep Learning algorithms require
much energy for computations, there are growing c... | 0 | zrz@andrew.cmu.edu [SEP] Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle : Deep Learning has enabled many advances in machine learning applications in
the last few years. However, since current Deep Learning algorithms require
much energy for computat... | 171 |
Learnable: Theory vs Applications | Two different views on machine learning problem: Applied learning (machine
learning with business applications) and Agnostic PAC learning are formalized
and compared here. I show that, under some conditions, the theory of PAC
Learnable provides a way to solve the Applied learning problem. However, the
theory requires t... | Liked | zrz@andrew.cmu.edu | Learnable: Theory vs Applications : Two different views on machine learning problem: Applied learning (machine
learning with business applications) and Agnostic PAC learning are formalized
and compared here. I show that, under some conditions, the theory of PAC
Learnable provides a way to solve the Applied learning pro... | 1 | zrz@andrew.cmu.edu [SEP] Learnable: Theory vs Applications : Two different views on machine learning problem: Applied learning (machine
learning with business applications) and Agnostic PAC learning are formalized
and compared here. I show that, under some conditions, the theory of PAC
Learnable provides a way to solve... | 144 |
WiCV 2019: The Sixth Women In Computer Vision Workshop | In this paper we present the Women in Computer Vision Workshop - WiCV 2019,
organized in conjunction with CVPR 2019. This event is meant for increasing the
visibility and inclusion of women researchers in the computer vision field.
Computer vision and machine learning have made incredible progress over the
past years, ... | Disliked | zrz@andrew.cmu.edu | WiCV 2019: The Sixth Women In Computer Vision Workshop : In this paper we present the Women in Computer Vision Workshop - WiCV 2019,
organized in conjunction with CVPR 2019. This event is meant for increasing the
visibility and inclusion of women researchers in the computer vision field.
Computer vision and machine lea... | 0 | zrz@andrew.cmu.edu [SEP] WiCV 2019: The Sixth Women In Computer Vision Workshop : In this paper we present the Women in Computer Vision Workshop - WiCV 2019,
organized in conjunction with CVPR 2019. This event is meant for increasing the
visibility and inclusion of women researchers in the computer vision field.
Comput... | 363 |
Design and Control of a Novel Six-Degree-of-Freedom Hybrid Robotic Arm | Robotic arms are key components in fruit-harvesting robots. In agricultural
settings, conventional serial or parallel robotic arms often fall short in
meeting the demands for a large workspace, rapid movement, enhanced capability
of obstacle avoidance and affordability. This study proposes a novel hybrid
six-degree-of-... | Liked | jechoi@andrew.cmu.edu | Design and Control of a Novel Six-Degree-of-Freedom Hybrid Robotic Arm : Robotic arms are key components in fruit-harvesting robots. In agricultural
settings, conventional serial or parallel robotic arms often fall short in
meeting the demands for a large workspace, rapid movement, enhanced capability
of obstacle avoid... | 1 | jechoi@andrew.cmu.edu [SEP] Design and Control of a Novel Six-Degree-of-Freedom Hybrid Robotic Arm : Robotic arms are key components in fruit-harvesting robots. In agricultural
settings, conventional serial or parallel robotic arms often fall short in
meeting the demands for a large workspace, rapid movement, enhanced ... | 413 |
Enhancing Robotic Arm Activity Recognition with Vision Transformers and Wavelet-Transformed Channel State Information | Vision-based methods are commonly used in robotic arm activity recognition.
These approaches typically rely on line-of-sight (LoS) and raise privacy
concerns, particularly in smart home applications. Passive Wi-Fi sensing
represents a new paradigm for recognizing human and robotic arm activities,
utilizing channel stat... | Liked | jechoi@andrew.cmu.edu | Enhancing Robotic Arm Activity Recognition with Vision Transformers and Wavelet-Transformed Channel State Information : Vision-based methods are commonly used in robotic arm activity recognition.
These approaches typically rely on line-of-sight (LoS) and raise privacy
concerns, particularly in smart home applications. ... | 1 | jechoi@andrew.cmu.edu [SEP] Enhancing Robotic Arm Activity Recognition with Vision Transformers and Wavelet-Transformed Channel State Information : Vision-based methods are commonly used in robotic arm activity recognition.
These approaches typically rely on line-of-sight (LoS) and raise privacy
concerns, particularly ... | 18 |
Vision-based Obstacle Removal System for Autonomous Ground Vehicles Using a Robotic Arm | Over the past few years, the use of camera-equipped robotic platforms for
data collection and visually monitoring applications has exponentially grown.
Cluttered construction sites with many objects (e.g., bricks, pipes, etc.) on
the ground are challenging environments for a mobile unmanned ground vehicle
(UGV) to navi... | Liked | jechoi@andrew.cmu.edu | Vision-based Obstacle Removal System for Autonomous Ground Vehicles Using a Robotic Arm : Over the past few years, the use of camera-equipped robotic platforms for
data collection and visually monitoring applications has exponentially grown.
Cluttered construction sites with many objects (e.g., bricks, pipes, etc.) on
... | 1 | jechoi@andrew.cmu.edu [SEP] Vision-based Obstacle Removal System for Autonomous Ground Vehicles Using a Robotic Arm : Over the past few years, the use of camera-equipped robotic platforms for
data collection and visually monitoring applications has exponentially grown.
Cluttered construction sites with many objects (e.... | 488 |
ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving | Offboard perception aims to automatically generate high-quality 3D labels for
autonomous driving (AD) scenes. Existing offboard methods focus on 3D object
detection with closed-set taxonomy and fail to match human-level recognition
capability on the rapidly evolving perception tasks. Due to heavy reliance on
human labe... | Disliked | zrz@andrew.cmu.edu | ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving : Offboard perception aims to automatically generate high-quality 3D labels for
autonomous driving (AD) scenes. Existing offboard methods focus on 3D object
detection with closed-set taxonomy and fail to match human-level recognition
cap... | 0 | zrz@andrew.cmu.edu [SEP] ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving : Offboard perception aims to automatically generate high-quality 3D labels for
autonomous driving (AD) scenes. Existing offboard methods focus on 3D object
detection with closed-set taxonomy and fail to match hu... | 315 |
Building Program Vector Representations for Deep Learning | Deep learning has made significant breakthroughs in various fields of
artificial intelligence. Advantages of deep learning include the ability to
capture highly complicated features, weak involvement of human engineering,
etc. However, it is still virtually impossible to use deep learning to analyze
programs since deep... | Liked | zrz@andrew.cmu.edu | Building Program Vector Representations for Deep Learning : Deep learning has made significant breakthroughs in various fields of
artificial intelligence. Advantages of deep learning include the ability to
capture highly complicated features, weak involvement of human engineering,
etc. However, it is still virtually im... | 1 | zrz@andrew.cmu.edu [SEP] Building Program Vector Representations for Deep Learning : Deep learning has made significant breakthroughs in various fields of
artificial intelligence. Advantages of deep learning include the ability to
capture highly complicated features, weak involvement of human engineering,
etc. However,... | 222 |
A Brief Survey of Deep Reinforcement Learning | Deep reinforcement learning is poised to revolutionise the field of AI and
represents a step towards building autonomous systems with a higher level
understanding of the visual world. Currently, deep learning is enabling
reinforcement learning to scale to problems that were previously intractable,
such as learning to p... | Liked | zrz@andrew.cmu.edu | A Brief Survey of Deep Reinforcement Learning : Deep reinforcement learning is poised to revolutionise the field of AI and
represents a step towards building autonomous systems with a higher level
understanding of the visual world. Currently, deep learning is enabling
reinforcement learning to scale to problems that we... | 1 | zrz@andrew.cmu.edu [SEP] A Brief Survey of Deep Reinforcement Learning : Deep reinforcement learning is poised to revolutionise the field of AI and
represents a step towards building autonomous systems with a higher level
understanding of the visual world. Currently, deep learning is enabling
reinforcement learning to ... | 189 |
RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins (early version) | 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 (early version) : 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 an... | 1 | jechoi@andrew.cmu.edu [SEP] RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins (early version) : 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-q... | 510 |
Latency-Aware Collaborative Perception | Collaborative perception has recently shown great potential to improve
perception capabilities over single-agent perception. Existing collaborative
perception methods usually consider an ideal communication environment.
However, in practice, the communication system inevitably suffers from latency
issues, causing poten... | Liked | zrz@andrew.cmu.edu | Latency-Aware Collaborative Perception : Collaborative perception has recently shown great potential to improve
perception capabilities over single-agent perception. Existing collaborative
perception methods usually consider an ideal communication environment.
However, in practice, the communication system inevitably s... | 1 | zrz@andrew.cmu.edu [SEP] Latency-Aware Collaborative Perception : Collaborative perception has recently shown great potential to improve
perception capabilities over single-agent perception. Existing collaborative
perception methods usually consider an ideal communication environment.
However, in practice, the communic... | 290 |
Robot Motion Prediction by Channel State Information | Autonomous robotic systems have gained a lot of attention, in recent years.
However, accurate prediction of robot motion in indoor environments with
limited visibility is challenging. While vision-based and light detection and
ranging (LiDAR) sensors are commonly used for motion detection and localization
of robotic ar... | Liked | jechoi@andrew.cmu.edu | Robot Motion Prediction by Channel State Information : Autonomous robotic systems have gained a lot of attention, in recent years.
However, accurate prediction of robot motion in indoor environments with
limited visibility is challenging. While vision-based and light detection and
ranging (LiDAR) sensors are commonly u... | 1 | jechoi@andrew.cmu.edu [SEP] Robot Motion Prediction by Channel State Information : Autonomous robotic systems have gained a lot of attention, in recent years.
However, accurate prediction of robot motion in indoor environments with
limited visibility is challenging. While vision-based and light detection and
ranging (L... | 506 |
A First Look at Deep Learning Apps on Smartphones | We are in the dawn of deep learning explosion for smartphones. To bridge the
gap between research and practice, we present the first empirical study on
16,500 the most popular Android apps, demystifying how smartphone apps exploit
deep learning in the wild. To this end, we build a new static tool that
dissects apps and... | Liked | zrz@andrew.cmu.edu | A First Look at Deep Learning Apps on Smartphones : We are in the dawn of deep learning explosion for smartphones. To bridge the
gap between research and practice, we present the first empirical study on
16,500 the most popular Android apps, demystifying how smartphone apps exploit
deep learning in the wild. To this en... | 1 | zrz@andrew.cmu.edu [SEP] A First Look at Deep Learning Apps on Smartphones : We are in the dawn of deep learning explosion for smartphones. To bridge the
gap between research and practice, we present the first empirical study on
16,500 the most popular Android apps, demystifying how smartphone apps exploit
deep learnin... | 157 |
Lecture Notes: Optimization for Machine Learning | Lecture notes on optimization for machine learning, derived from a course at
Princeton University and tutorials given in MLSS, Buenos Aires, as well as
Simons Foundation, Berkeley. | Disliked | zrz@andrew.cmu.edu | Lecture Notes: Optimization for Machine Learning : Lecture notes on optimization for machine learning, derived from a course at
Princeton University and tutorials given in MLSS, Buenos Aires, as well as
Simons Foundation, Berkeley. | 0 | zrz@andrew.cmu.edu [SEP] Lecture Notes: Optimization for Machine Learning : Lecture notes on optimization for machine learning, derived from a course at
Princeton University and tutorials given in MLSS, Buenos Aires, as well as
Simons Foundation, Berkeley. | 26 |
Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities | This keynote paper: presents a 21st century vision of computing; identifies
various computing paradigms promising to deliver the vision of computing
utilities; defines Cloud computing and provides the architecture for creating
market-oriented Clouds by leveraging technologies such as VMs; provides
thoughts on market-ba... | Disliked | zrz@andrew.cmu.edu | Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities : This keynote paper: presents a 21st century vision of computing; identifies
various computing paradigms promising to deliver the vision of computing
utilities; defines Cloud computing and provides the architec... | 0 | zrz@andrew.cmu.edu [SEP] Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities : This keynote paper: presents a 21st century vision of computing; identifies
various computing paradigms promising to deliver the vision of computing
utilities; defines Cloud computing ... | 385 |
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