Title string | Abstract string | Status string | User string | text string | label int64 | combined_text string | __index_level_0__ int64 |
|---|---|---|---|---|---|---|---|
A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion Perspective | 3D occupancy perception technology aims to observe and understand dense 3D
environments for autonomous vehicles. Owing to its comprehensive perception
capability, this technology is emerging as a trend in autonomous driving
perception systems, and is attracting significant attention from both industry
and academia. Sim... | Disliked | zrz@andrew.cmu.edu | A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion Perspective : 3D occupancy perception technology aims to observe and understand dense 3D
environments for autonomous vehicles. Owing to its comprehensive perception
capability, this technology is emerging as a trend in autonomous driving
pe... | 0 | zrz@andrew.cmu.edu [SEP] A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion Perspective : 3D occupancy perception technology aims to observe and understand dense 3D
environments for autonomous vehicles. Owing to its comprehensive perception
capability, this technology is emerging as a trend... | 292 |
Deep learning in radiology: an overview of the concepts and a survey of the state of the art | Deep learning is a branch of artificial intelligence where networks of simple
interconnected units are used to extract patterns from data in order to solve
complex problems. Deep learning algorithms have shown groundbreaking
performance in a variety of sophisticated tasks, especially those related to
images. They have ... | Liked | zrz@andrew.cmu.edu | Deep learning in radiology: an overview of the concepts and a survey of the state of the art : Deep learning is a branch of artificial intelligence where networks of simple
interconnected units are used to extract patterns from data in order to solve
complex problems. Deep learning algorithms have shown groundbreaking
... | 1 | zrz@andrew.cmu.edu [SEP] Deep learning in radiology: an overview of the concepts and a survey of the state of the art : Deep learning is a branch of artificial intelligence where networks of simple
interconnected units are used to extract patterns from data in order to solve
complex problems. Deep learning algorithms h... | 187 |
Deep Gaussian Mixture Models | Deep learning is a hierarchical inference method formed by subsequent
multiple layers of learning able to more efficiently describe complex
relationships. In this work, Deep Gaussian Mixture Models are introduced and
discussed. A Deep Gaussian Mixture model (DGMM) is a network of multiple layers
of latent variables, wh... | Disliked | zrz@andrew.cmu.edu | Deep Gaussian Mixture Models : Deep learning is a hierarchical inference method formed by subsequent
multiple layers of learning able to more efficiently describe complex
relationships. In this work, Deep Gaussian Mixture Models are introduced and
discussed. A Deep Gaussian Mixture model (DGMM) is a network of multiple... | 0 | zrz@andrew.cmu.edu [SEP] Deep Gaussian Mixture Models : Deep learning is a hierarchical inference method formed by subsequent
multiple layers of learning able to more efficiently describe complex
relationships. In this work, Deep Gaussian Mixture Models are introduced and
discussed. A Deep Gaussian Mixture model (DGMM)... | 262 |
Uniform vs. Lognormal Kinematics in Robots: Perceptual Preferences for Robotic Movements | Collaborative robots or cobots interact with humans in a common work
environment. In cobots, one under investigated but important issue is related
to their movement and how it is perceived by humans. This paper tries to
analyze whether humans prefer a robot moving in a human or in a robotic
fashion. To this end, the pr... | Liked | jechoi@andrew.cmu.edu | Uniform vs. Lognormal Kinematics in Robots: Perceptual Preferences for Robotic Movements : Collaborative robots or cobots interact with humans in a common work
environment. In cobots, one under investigated but important issue is related
to their movement and how it is perceived by humans. This paper tries to
analyze w... | 1 | jechoi@andrew.cmu.edu [SEP] Uniform vs. Lognormal Kinematics in Robots: Perceptual Preferences for Robotic Movements : Collaborative robots or cobots interact with humans in a common work
environment. In cobots, one under investigated but important issue is related
to their movement and how it is perceived by humans. T... | 551 |
Feature versus Raw Sequence: Deep Learning Comparative Study on Predicting Pre-miRNA | Should we input known genome sequence features or input sequence itself in
deep learning framework? As deep learning more popular in various applications,
researchers often come to question whether to generate features or use raw
sequences for deep learning. To answer this question, we study the prediction
accuracy of ... | Disliked | zrz@andrew.cmu.edu | Feature versus Raw Sequence: Deep Learning Comparative Study on Predicting Pre-miRNA : Should we input known genome sequence features or input sequence itself in
deep learning framework? As deep learning more popular in various applications,
researchers often come to question whether to generate features or use raw
seq... | 0 | zrz@andrew.cmu.edu [SEP] Feature versus Raw Sequence: Deep Learning Comparative Study on Predicting Pre-miRNA : Should we input known genome sequence features or input sequence itself in
deep learning framework? As deep learning more popular in various applications,
researchers often come to question whether to generat... | 178 |
Synchronized Multi-Arm Rearrangement Guided by Mode Graphs with Capacity Constraints | Solving task planning problems involving multiple objects and multiple
robotic arms poses scalability challenges. Such problems involve not only
coordinating multiple high-DoF arms, but also searching through possible
sequences of actions including object placements, and handoffs. The current
work identifies a useful c... | Disliked | jechoi@andrew.cmu.edu | Synchronized Multi-Arm Rearrangement Guided by Mode Graphs with Capacity Constraints : Solving task planning problems involving multiple objects and multiple
robotic arms poses scalability challenges. Such problems involve not only
coordinating multiple high-DoF arms, but also searching through possible
sequences of ac... | 0 | jechoi@andrew.cmu.edu [SEP] Synchronized Multi-Arm Rearrangement Guided by Mode Graphs with Capacity Constraints : Solving task planning problems involving multiple objects and multiple
robotic arms poses scalability challenges. Such problems involve not only
coordinating multiple high-DoF arms, but also searching thro... | 427 |
Probabilistic Machine Learning for Healthcare | Machine learning can be used to make sense of healthcare data. Probabilistic
machine learning models help provide a complete picture of observed data in
healthcare. In this review, we examine how probabilistic machine learning can
advance healthcare. We consider challenges in the predictive model building
pipeline wher... | Liked | zrz@andrew.cmu.edu | Probabilistic Machine Learning for Healthcare : Machine learning can be used to make sense of healthcare data. Probabilistic
machine learning models help provide a complete picture of observed data in
healthcare. In this review, we examine how probabilistic machine learning can
advance healthcare. We consider challenge... | 1 | zrz@andrew.cmu.edu [SEP] Probabilistic Machine Learning for Healthcare : Machine learning can be used to make sense of healthcare data. Probabilistic
machine learning models help provide a complete picture of observed data in
healthcare. In this review, we examine how probabilistic machine learning can
advance healthca... | 48 |
Priors in Bayesian Deep Learning: A Review | While the choice of prior is one of the most critical parts of the Bayesian
inference workflow, recent Bayesian deep learning models have often fallen back
on vague priors, such as standard Gaussians. In this review, we highlight the
importance of prior choices for Bayesian deep learning and present an overview
of diff... | Liked | zrz@andrew.cmu.edu | Priors in Bayesian Deep Learning: A Review : While the choice of prior is one of the most critical parts of the Bayesian
inference workflow, recent Bayesian deep learning models have often fallen back
on vague priors, such as standard Gaussians. In this review, we highlight the
importance of prior choices for Bayesian ... | 1 | zrz@andrew.cmu.edu [SEP] Priors in Bayesian Deep Learning: A Review : While the choice of prior is one of the most critical parts of the Bayesian
inference workflow, recent Bayesian deep learning models have often fallen back
on vague priors, such as standard Gaussians. In this review, we highlight the
importance of pr... | 213 |
SELM: Software Engineering of Machine Learning Models | One of the pillars of any machine learning model is its concepts. Using
software engineering, we can engineer these concepts and then develop and
expand them. In this article, we present a SELM framework for Software
Engineering of machine Learning Models. We then evaluate this framework through
a case study. Using the... | Disliked | zrz@andrew.cmu.edu | SELM: Software Engineering of Machine Learning Models : One of the pillars of any machine learning model is its concepts. Using
software engineering, we can engineer these concepts and then develop and
expand them. In this article, we present a SELM framework for Software
Engineering of machine Learning Models. We then... | 0 | zrz@andrew.cmu.edu [SEP] SELM: Software Engineering of Machine Learning Models : One of the pillars of any machine learning model is its concepts. Using
software engineering, we can engineer these concepts and then develop and
expand them. In this article, we present a SELM framework for Software
Engineering of machine... | 105 |
Automatic Design of Task-specific Robotic Arms | We present an interactive, computational design system for creating custom
robotic arms given high-level task descriptions and environmental constraints.
Various task requirements can be encoded as desired motion trajectories for the
robot arm's end-effector. Given such end-effector trajectories, our system
enables on-... | Liked | jechoi@andrew.cmu.edu | Automatic Design of Task-specific Robotic Arms : We present an interactive, computational design system for creating custom
robotic arms given high-level task descriptions and environmental constraints.
Various task requirements can be encoded as desired motion trajectories for the
robot arm's end-effector. Given such ... | 1 | jechoi@andrew.cmu.edu [SEP] Automatic Design of Task-specific Robotic Arms : We present an interactive, computational design system for creating custom
robotic arms given high-level task descriptions and environmental constraints.
Various task requirements can be encoded as desired motion trajectories for the
robot arm... | 387 |
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... | 396 |
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... | 24 |
Malleable Robots | This chapter is about the fundamentals of fabrication, control, and
human-robot interaction of a new type of collaborative robotic manipulators,
called malleable robots, which are based on adjustable architectures of varying
stiffness for achieving high dexterity with lower mobility arms. Collaborative
robots, or cobot... | Liked | jechoi@andrew.cmu.edu | Malleable Robots : This chapter is about the fundamentals of fabrication, control, and
human-robot interaction of a new type of collaborative robotic manipulators,
called malleable robots, which are based on adjustable architectures of varying
stiffness for achieving high dexterity with lower mobility arms. Collaborati... | 1 | jechoi@andrew.cmu.edu [SEP] Malleable Robots : This chapter is about the fundamentals of fabrication, control, and
human-robot interaction of a new type of collaborative robotic manipulators,
called malleable robots, which are based on adjustable architectures of varying
stiffness for achieving high dexterity with lowe... | 461 |
Design and Nonlinear Modeling of a Modular Cable Driven Soft Robotic Arm | We propose a novel multi-section cable-driven soft robotic arm inspired by
octopus tentacles along with a new modeling approach. Each section of the
modular manipulator is made of a soft tubing backbone, a soft silicon arm body,
and two rigid endcaps, which connect adjacent sections and decouple the
actuation cables of... | Liked | jechoi@andrew.cmu.edu | Design and Nonlinear Modeling of a Modular Cable Driven Soft Robotic Arm : We propose a novel multi-section cable-driven soft robotic arm inspired by
octopus tentacles along with a new modeling approach. Each section of the
modular manipulator is made of a soft tubing backbone, a soft silicon arm body,
and two rigid en... | 1 | jechoi@andrew.cmu.edu [SEP] Design and Nonlinear Modeling of a Modular Cable Driven Soft Robotic Arm : We propose a novel multi-section cable-driven soft robotic arm inspired by
octopus tentacles along with a new modeling approach. Each section of the
modular manipulator is made of a soft tubing backbone, a soft silico... | 549 |
DRO-EDL-MPC: Evidential Deep Learning-Based Distributionally Robust Model Predictive Control for Safe Autonomous Driving | Safety is a critical concern in motion planning for autonomous vehicles.
Modern autonomous vehicles rely on neural network-based perception, but making
control decisions based on these inference results poses significant safety
risks due to inherent uncertainties. To address this challenge, we present a
distributionall... | Liked | zrz@andrew.cmu.edu | DRO-EDL-MPC: Evidential Deep Learning-Based Distributionally Robust Model Predictive Control for Safe Autonomous Driving : Safety is a critical concern in motion planning for autonomous vehicles.
Modern autonomous vehicles rely on neural network-based perception, but making
control decisions based on these inference re... | 1 | zrz@andrew.cmu.edu [SEP] DRO-EDL-MPC: Evidential Deep Learning-Based Distributionally Robust Model Predictive Control for Safe Autonomous Driving : Safety is a critical concern in motion planning for autonomous vehicles.
Modern autonomous vehicles rely on neural network-based perception, but making
control decisions ba... | 324 |
Techniques for Automated Machine Learning | Automated machine learning (AutoML) aims to find optimal machine learning
solutions automatically given a machine learning problem. It could release the
burden of data scientists from the multifarious manual tuning process and
enable the access of domain experts to the off-the-shelf machine learning
solutions without e... | Liked | zrz@andrew.cmu.edu | Techniques for Automated Machine Learning : Automated machine learning (AutoML) aims to find optimal machine learning
solutions automatically given a machine learning problem. It could release the
burden of data scientists from the multifarious manual tuning process and
enable the access of domain experts to the off-th... | 1 | zrz@andrew.cmu.edu [SEP] Techniques for Automated Machine Learning : Automated machine learning (AutoML) aims to find optimal machine learning
solutions automatically given a machine learning problem. It could release the
burden of data scientists from the multifarious manual tuning process and
enable the access of dom... | 37 |
Multi-Arm Bin-Picking in Real-Time: A Combined Task and Motion Planning Approach | Automated bin-picking is a prerequisite for fully automated manufacturing and
warehouses. To successfully pick an item from an unstructured bin the robot
needs to first detect possible grasps for the objects, decide on the object to
remove and consequently plan and execute a feasible trajectory to retrieve the
chosen o... | Disliked | jechoi@andrew.cmu.edu | Multi-Arm Bin-Picking in Real-Time: A Combined Task and Motion Planning Approach : Automated bin-picking is a prerequisite for fully automated manufacturing and
warehouses. To successfully pick an item from an unstructured bin the robot
needs to first detect possible grasps for the objects, decide on the object to
remo... | 0 | jechoi@andrew.cmu.edu [SEP] Multi-Arm Bin-Picking in Real-Time: A Combined Task and Motion Planning Approach : Automated bin-picking is a prerequisite for fully automated manufacturing and
warehouses. To successfully pick an item from an unstructured bin the robot
needs to first detect possible grasps for the objects, ... | 445 |
Energy Optimized Robot Arm Path Planning using Differential Evolution in Dynamic Environment | Robots are widely used in industry due to their efficiency and high accuracy
in performance. One of the most intriguing issues in manufacturing stage of
production line is to minimize significantly high percentage of energy consumed
by these robot manipulators. The energy optimal control of robotic manipulators
is a co... | Liked | jechoi@andrew.cmu.edu | Energy Optimized Robot Arm Path Planning using Differential Evolution in Dynamic Environment : Robots are widely used in industry due to their efficiency and high accuracy
in performance. One of the most intriguing issues in manufacturing stage of
production line is to minimize significantly high percentage of energy c... | 1 | jechoi@andrew.cmu.edu [SEP] Energy Optimized Robot Arm Path Planning using Differential Evolution in Dynamic Environment : Robots are widely used in industry due to their efficiency and high accuracy
in performance. One of the most intriguing issues in manufacturing stage of
production line is to minimize significantly... | 527 |
Configuration-Aware Safe Control for Mobile Robotic Arm with Control Barrier Functions | Collision avoidance is a widely investigated topic in robotic applications.
When applying collision avoidance techniques to a mobile robot, how to deal
with the spatial structure of the robot still remains a challenge. In this
paper, we design a configuration-aware safe control law by solving a Quadratic
Programming (Q... | Liked | jechoi@andrew.cmu.edu | Configuration-Aware Safe Control for Mobile Robotic Arm with Control Barrier Functions : Collision avoidance is a widely investigated topic in robotic applications.
When applying collision avoidance techniques to a mobile robot, how to deal
with the spatial structure of the robot still remains a challenge. In this
pape... | 1 | jechoi@andrew.cmu.edu [SEP] Configuration-Aware Safe Control for Mobile Robotic Arm with Control Barrier Functions : Collision avoidance is a widely investigated topic in robotic applications.
When applying collision avoidance techniques to a mobile robot, how to deal
with the spatial structure of the robot still remai... | 420 |
A comprehensive review of Quantum Machine Learning: from NISQ to Fault Tolerance | Quantum machine learning, which involves running machine learning algorithms
on quantum devices, has garnered significant attention in both academic and
business circles. In this paper, we offer a comprehensive and unbiased review
of the various concepts that have emerged in the field of quantum machine
learning. This ... | Disliked | zrz@andrew.cmu.edu | A comprehensive review of Quantum Machine Learning: from NISQ to Fault Tolerance : Quantum machine learning, which involves running machine learning algorithms
on quantum devices, has garnered significant attention in both academic and
business circles. In this paper, we offer a comprehensive and unbiased review
of the... | 0 | zrz@andrew.cmu.edu [SEP] A comprehensive review of Quantum Machine Learning: from NISQ to Fault Tolerance : Quantum machine learning, which involves running machine learning algorithms
on quantum devices, has garnered significant attention in both academic and
business circles. In this paper, we offer a comprehensive a... | 53 |
Bandit-Based Model Selection for Deformable Object Manipulation | We present a novel approach to deformable object manipulation that does not
rely on highly-accurate modeling. The key contribution of this paper is to
formulate the task as a Multi-Armed Bandit problem, with each arm representing
a model of the deformable object. To "pull" an arm and evaluate its utility, we
use the ar... | Liked | jechoi@andrew.cmu.edu | Bandit-Based Model Selection for Deformable Object Manipulation : We present a novel approach to deformable object manipulation that does not
rely on highly-accurate modeling. The key contribution of this paper is to
formulate the task as a Multi-Armed Bandit problem, with each arm representing
a model of the deformabl... | 1 | jechoi@andrew.cmu.edu [SEP] Bandit-Based Model Selection for Deformable Object Manipulation : We present a novel approach to deformable object manipulation that does not
rely on highly-accurate modeling. The key contribution of this paper is to
formulate the task as a Multi-Armed Bandit problem, with each arm represent... | 473 |
Dynamic Balance Control of Multi-arm Free-Floating Space Robots | This paper investigates the problem of the dynamic balance control of
multi-arm free-floating space robot during capturing an active object in close
proximity. The position and orientation of space base will be affected during
the operation of space manipulator because of the dynamics coupling between the
manipulator a... | Liked | jechoi@andrew.cmu.edu | Dynamic Balance Control of Multi-arm Free-Floating Space Robots : This paper investigates the problem of the dynamic balance control of
multi-arm free-floating space robot during capturing an active object in close
proximity. The position and orientation of space base will be affected during
the operation of space mani... | 1 | jechoi@andrew.cmu.edu [SEP] Dynamic Balance Control of Multi-arm Free-Floating Space Robots : This paper investigates the problem of the dynamic balance control of
multi-arm free-floating space robot during capturing an active object in close
proximity. The position and orientation of space base will be affected during... | 13 |
Machine Learning using Stata/Python | We present two related Stata modules, r_ml_stata and c_ml_stata, for fitting
popular Machine Learning (ML) methods both in regression and classification
settings. Using the recent Stata/Python integration platform (sfi) of Stata 16,
these commands provide hyper-parameters' optimal tuning via K-fold
cross-validation usi... | Disliked | zrz@andrew.cmu.edu | Machine Learning using Stata/Python : We present two related Stata modules, r_ml_stata and c_ml_stata, for fitting
popular Machine Learning (ML) methods both in regression and classification
settings. Using the recent Stata/Python integration platform (sfi) of Stata 16,
these commands provide hyper-parameters' optimal ... | 0 | zrz@andrew.cmu.edu [SEP] Machine Learning using Stata/Python : We present two related Stata modules, r_ml_stata and c_ml_stata, for fitting
popular Machine Learning (ML) methods both in regression and classification
settings. Using the recent Stata/Python integration platform (sfi) of Stata 16,
these commands provide h... | 121 |
A Unified Framework of Deep Neural Networks by Capsules | With the growth of deep learning, how to describe deep neural networks
unifiedly is becoming an important issue. We first formalize neural networks
mathematically with their directed graph representations, and prove a
generation theorem about the induced networks of connected directed acyclic
graphs. Then, we set up a ... | Disliked | zrz@andrew.cmu.edu | A Unified Framework of Deep Neural Networks by Capsules : With the growth of deep learning, how to describe deep neural networks
unifiedly is becoming an important issue. We first formalize neural networks
mathematically with their directed graph representations, and prove a
generation theorem about the induced network... | 0 | zrz@andrew.cmu.edu [SEP] A Unified Framework of Deep Neural Networks by Capsules : With the growth of deep learning, how to describe deep neural networks
unifiedly is becoming an important issue. We first formalize neural networks
mathematically with their directed graph representations, and prove a
generation theorem ... | 172 |
A Transferable Legged Mobile Manipulation Framework Based on Disturbance Predictive Control | Due to their ability to adapt to different terrains, quadruped robots have
drawn much attention in the research field of robot learning. Legged mobile
manipulation, where a quadruped robot is equipped with a robotic arm, can
greatly enhance the performance of the robot in diverse manipulation tasks.
Several prior works... | Liked | jechoi@andrew.cmu.edu | A Transferable Legged Mobile Manipulation Framework Based on Disturbance Predictive Control : Due to their ability to adapt to different terrains, quadruped robots have
drawn much attention in the research field of robot learning. Legged mobile
manipulation, where a quadruped robot is equipped with a robotic arm, can
g... | 1 | jechoi@andrew.cmu.edu [SEP] A Transferable Legged Mobile Manipulation Framework Based on Disturbance Predictive Control : Due to their ability to adapt to different terrains, quadruped robots have
drawn much attention in the research field of robot learning. Legged mobile
manipulation, where a quadruped robot is equipp... | 505 |
Embodied Self-Supervised Learning (EMSSL) with Sampling and Training Coordination for Robot Arm Inverse Kinematics Model Learning | Forward and inverse kinematics models are fundamental to robot arms, serving
as the basis for the robot arm's operational tasks. However, in model learning
of robot arms, especially in the presence of redundant degrees of freedom,
inverse model learning is more challenging than forward model learning due to
the non-con... | Liked | jechoi@andrew.cmu.edu | Embodied Self-Supervised Learning (EMSSL) with Sampling and Training Coordination for Robot Arm Inverse Kinematics Model Learning : Forward and inverse kinematics models are fundamental to robot arms, serving
as the basis for the robot arm's operational tasks. However, in model learning
of robot arms, especially in the... | 1 | jechoi@andrew.cmu.edu [SEP] Embodied Self-Supervised Learning (EMSSL) with Sampling and Training Coordination for Robot Arm Inverse Kinematics Model Learning : Forward and inverse kinematics models are fundamental to robot arms, serving
as the basis for the robot arm's operational tasks. However, in model learning
of r... | 424 |
Can Machine Learning be Moral? | The ethics of Machine Learning has become an unavoidable topic in the AI
Community. The deployment of machine learning systems in multiple social
contexts has resulted in a closer ethical scrutiny of the design, development,
and application of these systems. The AI/ML community has come to terms with
the imperative to ... | Disliked | zrz@andrew.cmu.edu | Can Machine Learning be Moral? : The ethics of Machine Learning has become an unavoidable topic in the AI
Community. The deployment of machine learning systems in multiple social
contexts has resulted in a closer ethical scrutiny of the design, development,
and application of these systems. The AI/ML community has come... | 0 | zrz@andrew.cmu.edu [SEP] Can Machine Learning be Moral? : The ethics of Machine Learning has become an unavoidable topic in the AI
Community. The deployment of machine learning systems in multiple social
contexts has resulted in a closer ethical scrutiny of the design, development,
and application of these systems. The... | 95 |
Using Socially Expressive Mixed Reality Arms for Enhancing Low-Expressivity Robots | Expressivity--the use of multiple modalities to convey internal state and
intent of a robot--is critical for interaction. Yet, due to cost, safety, and
other constraints, many robots lack high degrees of physical expressivity. This
paper explores using mixed reality to enhance a robot with limited expressivity
by addin... | Liked | jechoi@andrew.cmu.edu | Using Socially Expressive Mixed Reality Arms for Enhancing Low-Expressivity Robots : Expressivity--the use of multiple modalities to convey internal state and
intent of a robot--is critical for interaction. Yet, due to cost, safety, and
other constraints, many robots lack high degrees of physical expressivity. This
pap... | 1 | jechoi@andrew.cmu.edu [SEP] Using Socially Expressive Mixed Reality Arms for Enhancing Low-Expressivity Robots : Expressivity--the use of multiple modalities to convey internal state and
intent of a robot--is critical for interaction. Yet, due to cost, safety, and
other constraints, many robots lack high degrees of phy... | 429 |
Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge | The limits of applicability of vision-and-language models are defined by the
coverage of their training data. Tasks like vision question answering (VQA)
often require commonsense and factual information beyond what can be learned
from task-specific datasets. This paper investigates the injection of knowledge
from gener... | Liked | zrz@andrew.cmu.edu | Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge : The limits of applicability of vision-and-language models are defined by the
coverage of their training data. Tasks like vision question answering (VQA)
often require commonsense and factual information beyond what can be learned
fro... | 1 | zrz@andrew.cmu.edu [SEP] Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge : The limits of applicability of vision-and-language models are defined by the
coverage of their training data. Tasks like vision question answering (VQA)
often require commonsense and factual information beyon... | 358 |
Aspects of Artificial Intelligence: Transforming Machine Learning Systems Naturally | In this paper, we study the machine learning elements which we are interested
in together as a machine learning system, consisting of a collection of machine
learning elements and a collection of relations between the elements. The
relations we concern are algebraic operations, binary relations, and binary
relations wi... | Liked | zrz@andrew.cmu.edu | Aspects of Artificial Intelligence: Transforming Machine Learning Systems Naturally : In this paper, we study the machine learning elements which we are interested
in together as a machine learning system, consisting of a collection of machine
learning elements and a collection of relations between the elements. The
re... | 1 | zrz@andrew.cmu.edu [SEP] Aspects of Artificial Intelligence: Transforming Machine Learning Systems Naturally : In this paper, we study the machine learning elements which we are interested
in together as a machine learning system, consisting of a collection of machine
learning elements and a collection of relations bet... | 115 |
A Unified Perception-Language-Action Framework for Adaptive Autonomous Driving | Autonomous driving systems face significant challenges in achieving
human-like adaptability, robustness, and interpretability in complex,
open-world environments. These challenges stem from fragmented architectures,
limited generalization to novel scenarios, and insufficient semantic extraction
from perception. To addr... | Liked | zrz@andrew.cmu.edu | A Unified Perception-Language-Action Framework for Adaptive Autonomous Driving : Autonomous driving systems face significant challenges in achieving
human-like adaptability, robustness, and interpretability in complex,
open-world environments. These challenges stem from fragmented architectures,
limited generalization ... | 1 | zrz@andrew.cmu.edu [SEP] A Unified Perception-Language-Action Framework for Adaptive Autonomous Driving : Autonomous driving systems face significant challenges in achieving
human-like adaptability, robustness, and interpretability in complex,
open-world environments. These challenges stem from fragmented architectures... | 325 |
Dynamic Balance Control of Multi-arm Free-Floating Space Robots | This paper investigates the problem of the dynamic balance control of
multi-arm free-floating space robot during capturing an active object in close
proximity. The position and orientation of space base will be affected during
the operation of space manipulator because of the dynamics coupling between the
manipulator a... | Disliked | jechoi@andrew.cmu.edu | Dynamic Balance Control of Multi-arm Free-Floating Space Robots : This paper investigates the problem of the dynamic balance control of
multi-arm free-floating space robot during capturing an active object in close
proximity. The position and orientation of space base will be affected during
the operation of space mani... | 0 | jechoi@andrew.cmu.edu [SEP] Dynamic Balance Control of Multi-arm Free-Floating Space Robots : This paper investigates the problem of the dynamic balance control of
multi-arm free-floating space robot during capturing an active object in close
proximity. The position and orientation of space base will be affected during... | 397 |
Robotic Arm for Remote Surgery | Recent advances in telecommunications have enabled surgeons to operate
remotely on patients with the use of robotics. The investigation and testing of
remote surgery using a robotic arm is presented. The robotic arm is designed to
have four degrees of freedom that track the surgeon's x, y, z positions and the
rotation ... | Liked | jechoi@andrew.cmu.edu | Robotic Arm for Remote Surgery : Recent advances in telecommunications have enabled surgeons to operate
remotely on patients with the use of robotics. The investigation and testing of
remote surgery using a robotic arm is presented. The robotic arm is designed to
have four degrees of freedom that track the surgeon's x,... | 1 | jechoi@andrew.cmu.edu [SEP] Robotic Arm for Remote Surgery : Recent advances in telecommunications have enabled surgeons to operate
remotely on patients with the use of robotics. The investigation and testing of
remote surgery using a robotic arm is presented. The robotic arm is designed to
have four degrees of freedom... | 482 |
BMVC 2019: Workshop on Interpretable and Explainable Machine Vision | Proceedings of the BMVC 2019 Workshop on Interpretable and Explainable
Machine Vision, Cardiff, UK, September 12, 2019. | Disliked | zrz@andrew.cmu.edu | BMVC 2019: Workshop on Interpretable and Explainable Machine Vision : Proceedings of the BMVC 2019 Workshop on Interpretable and Explainable
Machine Vision, Cardiff, UK, September 12, 2019. | 0 | zrz@andrew.cmu.edu [SEP] BMVC 2019: Workshop on Interpretable and Explainable Machine Vision : Proceedings of the BMVC 2019 Workshop on Interpretable and Explainable
Machine Vision, Cardiff, UK, September 12, 2019. | 344 |
Procams-Based Cybernetics | Procams-based cybernetics is a unique, emerging research field, which aims at
enhancing and supporting our activities by naturally connecting human and
computers/machines as a cooperative integrated system via projector-camera
systems (procams). It rests on various research domains such as
virtual/augmented reality, co... | Disliked | zrz@andrew.cmu.edu | Procams-Based Cybernetics : Procams-based cybernetics is a unique, emerging research field, which aims at
enhancing and supporting our activities by naturally connecting human and
computers/machines as a cooperative integrated system via projector-camera
systems (procams). It rests on various research domains such as
v... | 0 | zrz@andrew.cmu.edu [SEP] Procams-Based Cybernetics : Procams-based cybernetics is a unique, emerging research field, which aims at
enhancing and supporting our activities by naturally connecting human and
computers/machines as a cooperative integrated system via projector-camera
systems (procams). It rests on various r... | 383 |
Recent Advances in Deep Learning: An Overview | Deep Learning is one of the newest trends in Machine Learning and Artificial
Intelligence research. It is also one of the most popular scientific research
trends now-a-days. Deep learning methods have brought revolutionary advances in
computer vision and machine learning. Every now and then, new and new deep
learning t... | Liked | zrz@andrew.cmu.edu | Recent Advances in Deep Learning: An Overview : Deep Learning is one of the newest trends in Machine Learning and Artificial
Intelligence research. It is also one of the most popular scientific research
trends now-a-days. Deep learning methods have brought revolutionary advances in
computer vision and machine learning.... | 1 | zrz@andrew.cmu.edu [SEP] Recent Advances in Deep Learning: An Overview : Deep Learning is one of the newest trends in Machine Learning and Artificial
Intelligence research. It is also one of the most popular scientific research
trends now-a-days. Deep learning methods have brought revolutionary advances in
computer vis... | 230 |
Efficient Detection of Objects Near a Robot Manipulator via Miniature Time-of-Flight Sensors | We provide a method for detecting and localizing objects near a robot arm
using arm-mounted miniature time-of-flight sensors. A key challenge when using
arm-mounted sensors is differentiating between the robot itself and external
objects in sensor measurements. To address this challenge, we propose a
computationally li... | Liked | jechoi@andrew.cmu.edu | Efficient Detection of Objects Near a Robot Manipulator via Miniature Time-of-Flight Sensors : We provide a method for detecting and localizing objects near a robot arm
using arm-mounted miniature time-of-flight sensors. A key challenge when using
arm-mounted sensors is differentiating between the robot itself and exte... | 1 | jechoi@andrew.cmu.edu [SEP] Efficient Detection of Objects Near a Robot Manipulator via Miniature Time-of-Flight Sensors : We provide a method for detecting and localizing objects near a robot arm
using arm-mounted miniature time-of-flight sensors. A key challenge when using
arm-mounted sensors is differentiating betwe... | 418 |
Distributed Multi-Task Learning with Shared Representation | We study the problem of distributed multi-task learning with shared
representation, where each machine aims to learn a separate, but related, task
in an unknown shared low-dimensional subspaces, i.e. when the predictor matrix
has low rank. We consider a setting where each task is handled by a different
machine, with sa... | Liked | zrz@andrew.cmu.edu | Distributed Multi-Task Learning with Shared Representation : We study the problem of distributed multi-task learning with shared
representation, where each machine aims to learn a separate, but related, task
in an unknown shared low-dimensional subspaces, i.e. when the predictor matrix
has low rank. We consider a setti... | 1 | zrz@andrew.cmu.edu [SEP] Distributed Multi-Task Learning with Shared Representation : We study the problem of distributed multi-task learning with shared
representation, where each machine aims to learn a separate, but related, task
in an unknown shared low-dimensional subspaces, i.e. when the predictor matrix
has low ... | 54 |
Four-Arm Collaboration: Two Dual-Arm Robots Work Together to Maneuver Tethered Tools | In this paper, we present a planner for a master dual-arm robot to manipulate
tethered tools with an assistant dual-arm robot's help. The assistant robot
provides assistance to the master robot by manipulating the tool cable and
avoiding collisions. The provided assistance allows the master robot to perform
tool placem... | Disliked | jechoi@andrew.cmu.edu | Four-Arm Collaboration: Two Dual-Arm Robots Work Together to Maneuver Tethered Tools : In this paper, we present a planner for a master dual-arm robot to manipulate
tethered tools with an assistant dual-arm robot's help. The assistant robot
provides assistance to the master robot by manipulating the tool cable and
avoi... | 0 | jechoi@andrew.cmu.edu [SEP] Four-Arm Collaboration: Two Dual-Arm Robots Work Together to Maneuver Tethered Tools : In this paper, we present a planner for a master dual-arm robot to manipulate
tethered tools with an assistant dual-arm robot's help. The assistant robot
provides assistance to the master robot by manipula... | 16 |
Multi-Objective Trajectory Planning for a Robotic Arm in Curtain Wall Installation | In the context of labor shortages and rising costs, construction robots are
regarded as the key to revolutionizing traditional construction methods and
improving efficiency and quality in the construction industry. In order to
ensure that construction robots can perform tasks efficiently and accurately in
complex const... | Liked | jechoi@andrew.cmu.edu | Multi-Objective Trajectory Planning for a Robotic Arm in Curtain Wall Installation : In the context of labor shortages and rising costs, construction robots are
regarded as the key to revolutionizing traditional construction methods and
improving efficiency and quality in the construction industry. In order to
ensure t... | 1 | jechoi@andrew.cmu.edu [SEP] Multi-Objective Trajectory Planning for a Robotic Arm in Curtain Wall Installation : In the context of labor shortages and rising costs, construction robots are
regarded as the key to revolutionizing traditional construction methods and
improving efficiency and quality in the construction in... | 523 |
Deep Learning for Epidemiologists: An Introduction to Neural Networks | Deep learning methods are increasingly being applied to problems in medicine
and healthcare. However, few epidemiologists have received formal training in
these methods. To bridge this gap, this article introduces to the fundamentals
of deep learning from an epidemiological perspective. Specifically, this
article revie... | Liked | zrz@andrew.cmu.edu | Deep Learning for Epidemiologists: An Introduction to Neural Networks : Deep learning methods are increasingly being applied to problems in medicine
and healthcare. However, few epidemiologists have received formal training in
these methods. To bridge this gap, this article introduces to the fundamentals
of deep learni... | 1 | zrz@andrew.cmu.edu [SEP] Deep Learning for Epidemiologists: An Introduction to Neural Networks : Deep learning methods are increasingly being applied to problems in medicine
and healthcare. However, few epidemiologists have received formal training in
these methods. To bridge this gap, this article introduces to the fu... | 216 |
A Survey of Deep Learning Based Software Refactoring | Refactoring is one of the most important activities in software engineering
which is used to improve the quality of a software system. With the advancement
of deep learning techniques, researchers are attempting to apply deep learning
techniques to software refactoring. Consequently, dozens of deep learning-based
refac... | Liked | zrz@andrew.cmu.edu | A Survey of Deep Learning Based Software Refactoring : Refactoring is one of the most important activities in software engineering
which is used to improve the quality of a software system. With the advancement
of deep learning techniques, researchers are attempting to apply deep learning
techniques to software refacto... | 1 | zrz@andrew.cmu.edu [SEP] A Survey of Deep Learning Based Software Refactoring : Refactoring is one of the most important activities in software engineering
which is used to improve the quality of a software system. With the advancement
of deep learning techniques, researchers are attempting to apply deep learning
techn... | 236 |
Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks | A big convergence of language, vision, and multimodal pretraining is
emerging. In this work, we introduce a general-purpose multimodal foundation
model BEiT-3, which achieves state-of-the-art transfer performance on both
vision and vision-language tasks. Specifically, we advance the big convergence
from three aspects: ... | Liked | zrz@andrew.cmu.edu | Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks : A big convergence of language, vision, and multimodal pretraining is
emerging. In this work, we introduce a general-purpose multimodal foundation
model BEiT-3, which achieves state-of-the-art transfer performance on both
vision and... | 1 | zrz@andrew.cmu.edu [SEP] Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks : A big convergence of language, vision, and multimodal pretraining is
emerging. In this work, we introduce a general-purpose multimodal foundation
model BEiT-3, which achieves state-of-the-art transfer perfo... | 378 |
Finding shorter paths for robot arms using their redundancy | Many robot arms can accomplish one task using many different joint
configurations. Often only one of these configurations is used as a goal by the
path planner. Ideally the robot's path planner would be able to use the extra
configurations to find higher quality paths. In this paper we use the extra
goal configurations... | Liked | jechoi@andrew.cmu.edu | Finding shorter paths for robot arms using their redundancy : Many robot arms can accomplish one task using many different joint
configurations. Often only one of these configurations is used as a goal by the
path planner. Ideally the robot's path planner would be able to use the extra
configurations to find higher qua... | 1 | jechoi@andrew.cmu.edu [SEP] Finding shorter paths for robot arms using their redundancy : Many robot arms can accomplish one task using many different joint
configurations. Often only one of these configurations is used as a goal by the
path planner. Ideally the robot's path planner would be able to use the extra
confi... | 446 |
Learning and Composing Primitive Skills for Dual-arm Manipulation | In an attempt to confer robots with complex manipulation capabilities,
dual-arm anthropomorphic systems have become an important research topic in the
robotics community. Most approaches in the literature rely upon a great
understanding of the dynamics underlying the system's behaviour and yet offer
limited autonomous ... | Liked | jechoi@andrew.cmu.edu | Learning and Composing Primitive Skills for Dual-arm Manipulation : In an attempt to confer robots with complex manipulation capabilities,
dual-arm anthropomorphic systems have become an important research topic in the
robotics community. Most approaches in the literature rely upon a great
understanding of the dynamics... | 1 | jechoi@andrew.cmu.edu [SEP] Learning and Composing Primitive Skills for Dual-arm Manipulation : In an attempt to confer robots with complex manipulation capabilities,
dual-arm anthropomorphic systems have become an important research topic in the
robotics community. Most approaches in the literature rely upon a great
u... | 535 |
Deep learning research landscape & roadmap in a nutshell: past, present and future -- Towards deep cortical learning | The past, present and future of deep learning is presented in this work.
Given this landscape & roadmap, we predict that deep cortical learning will be
the convergence of deep learning & cortical learning which builds an artificial
cortical column ultimately. | Liked | zrz@andrew.cmu.edu | Deep learning research landscape & roadmap in a nutshell: past, present and future -- Towards deep cortical learning : The past, present and future of deep learning is presented in this work.
Given this landscape & roadmap, we predict that deep cortical learning will be
the convergence of deep learning & cortical learn... | 1 | zrz@andrew.cmu.edu [SEP] Deep learning research landscape & roadmap in a nutshell: past, present and future -- Towards deep cortical learning : The past, present and future of deep learning is presented in this work.
Given this landscape & roadmap, we predict that deep cortical learning will be
the convergence of deep ... | 156 |
Selective Communication for Cooperative Perception in End-to-End Autonomous Driving | The reliability of current autonomous driving systems is often jeopardized in
situations when the vehicle's field-of-view is limited by nearby occluding
objects. To mitigate this problem, vehicle-to-vehicle communication to share
sensor information among multiple autonomous driving vehicles has been
proposed. However, ... | Disliked | zrz@andrew.cmu.edu | Selective Communication for Cooperative Perception in End-to-End Autonomous Driving : The reliability of current autonomous driving systems is often jeopardized in
situations when the vehicle's field-of-view is limited by nearby occluding
objects. To mitigate this problem, vehicle-to-vehicle communication to share
sens... | 0 | zrz@andrew.cmu.edu [SEP] Selective Communication for Cooperative Perception in End-to-End Autonomous Driving : The reliability of current autonomous driving systems is often jeopardized in
situations when the vehicle's field-of-view is limited by nearby occluding
objects. To mitigate this problem, vehicle-to-vehicle co... | 323 |
Deep Learning and Its Applications to Machine Health Monitoring: A Survey | Since 2006, deep learning (DL) has become a rapidly growing research
direction, redefining state-of-the-art performances in a wide range of areas
such as object recognition, image segmentation, speech recognition and machine
translation. In modern manufacturing systems, data-driven machine health
monitoring is gaining ... | Disliked | zrz@andrew.cmu.edu | Deep Learning and Its Applications to Machine Health Monitoring: A Survey : Since 2006, deep learning (DL) has become a rapidly growing research
direction, redefining state-of-the-art performances in a wide range of areas
such as object recognition, image segmentation, speech recognition and machine
translation. In mod... | 0 | zrz@andrew.cmu.edu [SEP] Deep Learning and Its Applications to Machine Health Monitoring: A Survey : Since 2006, deep learning (DL) has become a rapidly growing research
direction, redefining state-of-the-art performances in a wide range of areas
such as object recognition, image segmentation, speech recognition and ma... | 137 |
Embed System for Robotic Arm with 3 Degree of Freedom Controller using Computational Vision on Real-Time | This Paper deals with robotic arm embed controller system, with distributed
system based on protocol communication between one server supporting multiple
points and mobile applications trough sockets .The proposed system utilizes
hand with glove gesture in three-dimensional recognition using fuzzy
implementation to set... | Liked | jechoi@andrew.cmu.edu | Embed System for Robotic Arm with 3 Degree of Freedom Controller using Computational Vision on Real-Time : This Paper deals with robotic arm embed controller system, with distributed
system based on protocol communication between one server supporting multiple
points and mobile applications trough sockets .The proposed... | 1 | jechoi@andrew.cmu.edu [SEP] Embed System for Robotic Arm with 3 Degree of Freedom Controller using Computational Vision on Real-Time : This Paper deals with robotic arm embed controller system, with distributed
system based on protocol communication between one server supporting multiple
points and mobile applications ... | 430 |
Naturalistic Robot Arm Trajectory Generation via Representation Learning | The integration of manipulator robots in household environments suggests a
need for more predictable and human-like robot motion. This holds especially
true for wheelchair-mounted assistive robots that can support the independence
of people with paralysis. One method of generating naturalistic motion
trajectories is vi... | Liked | jechoi@andrew.cmu.edu | Naturalistic Robot Arm Trajectory Generation via Representation Learning : The integration of manipulator robots in household environments suggests a
need for more predictable and human-like robot motion. This holds especially
true for wheelchair-mounted assistive robots that can support the independence
of people with... | 1 | jechoi@andrew.cmu.edu [SEP] Naturalistic Robot Arm Trajectory Generation via Representation Learning : The integration of manipulator robots in household environments suggests a
need for more predictable and human-like robot motion. This holds especially
true for wheelchair-mounted assistive robots that can support the... | 490 |
Automated Lane Change Behavior Prediction and Environmental Perception Based on SLAM Technology | In addition to environmental perception sensors such as cameras, radars, etc.
in the automatic driving system, the external environment of the vehicle is
perceived, in fact, there is also a perception sensor that has been silently
dedicated in the system, that is, the positioning module. This paper explores
the applica... | Liked | zrz@andrew.cmu.edu | Automated Lane Change Behavior Prediction and Environmental Perception Based on SLAM Technology : In addition to environmental perception sensors such as cameras, radars, etc.
in the automatic driving system, the external environment of the vehicle is
perceived, in fact, there is also a perception sensor that has been ... | 1 | zrz@andrew.cmu.edu [SEP] Automated Lane Change Behavior Prediction and Environmental Perception Based on SLAM Technology : In addition to environmental perception sensors such as cameras, radars, etc.
in the automatic driving system, the external environment of the vehicle is
perceived, in fact, there is also a percept... | 318 |
Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology | Machine learning is an established and frequently used technique in industry
and academia but a standard process model to improve success and efficiency of
machine learning applications is still missing. Project organizations and
machine learning practitioners have a need for guidance throughout the life
cycle of a mac... | Liked | zrz@andrew.cmu.edu | Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology : Machine learning is an established and frequently used technique in industry
and academia but a standard process model to improve success and efficiency of
machine learning applications is still missing. Project organizations and... | 1 | zrz@andrew.cmu.edu [SEP] Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology : Machine learning is an established and frequently used technique in industry
and academia but a standard process model to improve success and efficiency of
machine learning applications is still missing. ... | 50 |
Learning Theory and Support Vector Machines - a primer | The main goal of statistical learning theory is to provide a fundamental
framework for the problem of decision making and model construction based on
sets of data. Here, we present a brief introduction to the fundamentals of
statistical learning theory, in particular the difference between empirical and
structural risk... | Disliked | zrz@andrew.cmu.edu | Learning Theory and Support Vector Machines - a primer : The main goal of statistical learning theory is to provide a fundamental
framework for the problem of decision making and model construction based on
sets of data. Here, we present a brief introduction to the fundamentals of
statistical learning theory, in partic... | 0 | zrz@andrew.cmu.edu [SEP] Learning Theory and Support Vector Machines - a primer : The main goal of statistical learning theory is to provide a fundamental
framework for the problem of decision making and model construction based on
sets of data. Here, we present a brief introduction to the fundamentals of
statistical l... | 119 |
Is Multimodal Vision Supervision Beneficial to Language? | Vision (image and video) - Language (VL) pre-training is the recent popular
paradigm that achieved state-of-the-art results on multi-modal tasks like
image-retrieval, video-retrieval, visual question answering etc. These models
are trained in an unsupervised way and greatly benefit from the complementary
modality super... | Disliked | zrz@andrew.cmu.edu | Is Multimodal Vision Supervision Beneficial to Language? : Vision (image and video) - Language (VL) pre-training is the recent popular
paradigm that achieved state-of-the-art results on multi-modal tasks like
image-retrieval, video-retrieval, visual question answering etc. These models
are trained in an unsupervised wa... | 0 | zrz@andrew.cmu.edu [SEP] Is Multimodal Vision Supervision Beneficial to Language? : Vision (image and video) - Language (VL) pre-training is the recent popular
paradigm that achieved state-of-the-art results on multi-modal tasks like
image-retrieval, video-retrieval, visual question answering etc. These models
are trai... | 370 |
Affordance-Aware Handovers with Human Arm Mobility Constraints | Reasoning about object handover configurations allows an assistive agent to
estimate the appropriateness of handover for a receiver with different arm
mobility capacities. While there are existing approaches for estimating the
effectiveness of handovers, their findings are limited to users without arm
mobility impairme... | Liked | jechoi@andrew.cmu.edu | Affordance-Aware Handovers with Human Arm Mobility Constraints : Reasoning about object handover configurations allows an assistive agent to
estimate the appropriateness of handover for a receiver with different arm
mobility capacities. While there are existing approaches for estimating the
effectiveness of handovers, ... | 1 | jechoi@andrew.cmu.edu [SEP] Affordance-Aware Handovers with Human Arm Mobility Constraints : Reasoning about object handover configurations allows an assistive agent to
estimate the appropriateness of handover for a receiver with different arm
mobility capacities. While there are existing approaches for estimating the
... | 550 |
Machine Learning Potential Repository | This paper introduces a machine learning potential repository that includes
Pareto optimal machine learning potentials. It also shows the systematic
development of accurate and fast machine learning potentials for a wide range
of elemental systems. As a result, many Pareto optimal machine learning
potentials are availa... | Disliked | zrz@andrew.cmu.edu | Machine Learning Potential Repository : This paper introduces a machine learning potential repository that includes
Pareto optimal machine learning potentials. It also shows the systematic
development of accurate and fast machine learning potentials for a wide range
of elemental systems. As a result, many Pareto optima... | 0 | zrz@andrew.cmu.edu [SEP] Machine Learning Potential Repository : This paper introduces a machine learning potential repository that includes
Pareto optimal machine learning potentials. It also shows the systematic
development of accurate and fast machine learning potentials for a wide range
of elemental systems. As a r... | 62 |
Deep Learning in the Field of Biometric Template Protection: An Overview | Today, deep learning represents the most popular and successful form of
machine learning. Deep learning has revolutionised the field of pattern
recognition, including biometric recognition. Biometric systems utilising deep
learning have been shown to achieve auspicious recognition accuracy, surpassing
human performance... | Disliked | zrz@andrew.cmu.edu | Deep Learning in the Field of Biometric Template Protection: An Overview : Today, deep learning represents the most popular and successful form of
machine learning. Deep learning has revolutionised the field of pattern
recognition, including biometric recognition. Biometric systems utilising deep
learning have been sho... | 0 | zrz@andrew.cmu.edu [SEP] Deep Learning in the Field of Biometric Template Protection: An Overview : Today, deep learning represents the most popular and successful form of
machine learning. Deep learning has revolutionised the field of pattern
recognition, including biometric recognition. Biometric systems utilising de... | 173 |
Risk-Averse Biased Human Policies in Assistive Multi-Armed Bandit Settings | Assistive multi-armed bandit problems can be used to model team situations
between a human and an autonomous system like a domestic service robot. To
account for human biases such as the risk-aversion described in the Cumulative
Prospect Theory, the setting is expanded to using observable rewards. When
robots leverage ... | Disliked | jechoi@andrew.cmu.edu | Risk-Averse Biased Human Policies in Assistive Multi-Armed Bandit Settings : Assistive multi-armed bandit problems can be used to model team situations
between a human and an autonomous system like a domestic service robot. To
account for human biases such as the risk-aversion described in the Cumulative
Prospect Theor... | 0 | jechoi@andrew.cmu.edu [SEP] Risk-Averse Biased Human Policies in Assistive Multi-Armed Bandit Settings : Assistive multi-armed bandit problems can be used to model team situations
between a human and an autonomous system like a domestic service robot. To
account for human biases such as the risk-aversion described in t... | 518 |
Private Machine Learning via Randomised Response | We introduce a general learning framework for private machine learning based
on randomised response. Our assumption is that all actors are potentially
adversarial and as such we trust only to release a single noisy version of an
individual's datapoint. We discuss a general approach that forms a consistent
way to estima... | Disliked | zrz@andrew.cmu.edu | Private Machine Learning via Randomised Response : We introduce a general learning framework for private machine learning based
on randomised response. Our assumption is that all actors are potentially
adversarial and as such we trust only to release a single noisy version of an
individual's datapoint. We discuss a gen... | 0 | zrz@andrew.cmu.edu [SEP] Private Machine Learning via Randomised Response : We introduce a general learning framework for private machine learning based
on randomised response. Our assumption is that all actors are potentially
adversarial and as such we trust only to release a single noisy version of an
individual's da... | 46 |
The configuration space of planar spidery linkages | The configuration space of the mechanism of a planar robot is studied. We
consider a robot which has $n$ arms such that each arm is of length 1+1 and has
a rotational joint in the middle, and that the endpoint of the $k$-th arm is
fixed to $Re^{\frac{2(k-1)\pi}ni}$. Generically, the configuration space is
diffeomorphic... | Liked | jechoi@andrew.cmu.edu | The configuration space of planar spidery linkages : The configuration space of the mechanism of a planar robot is studied. We
consider a robot which has $n$ arms such that each arm is of length 1+1 and has
a rotational joint in the middle, and that the endpoint of the $k$-th arm is
fixed to $Re^{\frac{2(k-1)\pi}ni}$. ... | 1 | jechoi@andrew.cmu.edu [SEP] The configuration space of planar spidery linkages : The configuration space of the mechanism of a planar robot is studied. We
consider a robot which has $n$ arms such that each arm is of length 1+1 and has
a rotational joint in the middle, and that the endpoint of the $k$-th arm is
fixed to... | 566 |
Seven Myths in Machine Learning Research | We present seven myths commonly believed to be true in machine learning
research, circa Feb 2019. This is an archival copy of the blog post at
https://crazyoscarchang.github.io/2019/02/16/seven-myths-in-machine-learning-research/
Myth 1: TensorFlow is a Tensor manipulation library
Myth 2: Image datasets are represe... | Liked | zrz@andrew.cmu.edu | Seven Myths in Machine Learning Research : We present seven myths commonly believed to be true in machine learning
research, circa Feb 2019. This is an archival copy of the blog post at
https://crazyoscarchang.github.io/2019/02/16/seven-myths-in-machine-learning-research/
Myth 1: TensorFlow is a Tensor manipulation l... | 1 | zrz@andrew.cmu.edu [SEP] Seven Myths in Machine Learning Research : We present seven myths commonly believed to be true in machine learning
research, circa Feb 2019. This is an archival copy of the blog post at
https://crazyoscarchang.github.io/2019/02/16/seven-myths-in-machine-learning-research/
Myth 1: TensorFlow i... | 152 |
Information Processing Capability of Soft Continuum Arms | Soft Continuum arms, such as trunk and tentacle robots, can be considered as
the "dual" of traditional rigid-bodied robots in terms of manipulability,
degrees of freedom, and compliance. Introduced two decades ago, continuum arms
have not yet realized their full potential, and largely remain as laboratory
curiosities. ... | Liked | jechoi@andrew.cmu.edu | Information Processing Capability of Soft Continuum Arms : Soft Continuum arms, such as trunk and tentacle robots, can be considered as
the "dual" of traditional rigid-bodied robots in terms of manipulability,
degrees of freedom, and compliance. Introduced two decades ago, continuum arms
have not yet realized their ful... | 1 | jechoi@andrew.cmu.edu [SEP] Information Processing Capability of Soft Continuum Arms : Soft Continuum arms, such as trunk and tentacle robots, can be considered as
the "dual" of traditional rigid-bodied robots in terms of manipulability,
degrees of freedom, and compliance. Introduced two decades ago, continuum arms
hav... | 474 |
F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Clouds | Autonomous vehicles are heavily reliant upon their sensors to perfect the
perception of surrounding environments, however, with the current state of
technology, the data which a vehicle uses is confined to that from its own
sensors. Data sharing between vehicles and/or edge servers is limited by the
available network b... | Disliked | zrz@andrew.cmu.edu | F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Clouds : Autonomous vehicles are heavily reliant upon their sensors to perfect the
perception of surrounding environments, however, with the current state of
technology, the data which a vehicle uses is confined t... | 0 | zrz@andrew.cmu.edu [SEP] F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Clouds : Autonomous vehicles are heavily reliant upon their sensors to perfect the
perception of surrounding environments, however, with the current state of
technology, the data which a v... | 317 |
Modeling Perception Errors towards Robust Decision Making in Autonomous Vehicles | Sensing and Perception (S&P) is a crucial component of an autonomous system
(such as a robot), especially when deployed in highly dynamic environments
where it is required to react to unexpected situations. This is particularly
true in case of Autonomous Vehicles (AVs) driving on public roads. However, the
current eval... | Disliked | zrz@andrew.cmu.edu | Modeling Perception Errors towards Robust Decision Making in Autonomous Vehicles : Sensing and Perception (S&P) is a crucial component of an autonomous system
(such as a robot), especially when deployed in highly dynamic environments
where it is required to react to unexpected situations. This is particularly
true in c... | 0 | zrz@andrew.cmu.edu [SEP] Modeling Perception Errors towards Robust Decision Making in Autonomous Vehicles : Sensing and Perception (S&P) is a crucial component of an autonomous system
(such as a robot), especially when deployed in highly dynamic environments
where it is required to react to unexpected situations. This ... | 297 |
AutoCompete: A Framework for Machine Learning Competition | In this paper, we propose AutoCompete, a highly automated machine learning
framework for tackling machine learning competitions. This framework has been
learned by us, validated and improved over a period of more than two years by
participating in online machine learning competitions. It aims at minimizing
human interf... | Disliked | zrz@andrew.cmu.edu | AutoCompete: A Framework for Machine Learning Competition : In this paper, we propose AutoCompete, a highly automated machine learning
framework for tackling machine learning competitions. This framework has been
learned by us, validated and improved over a period of more than two years by
participating in online machi... | 0 | zrz@andrew.cmu.edu [SEP] AutoCompete: A Framework for Machine Learning Competition : In this paper, we propose AutoCompete, a highly automated machine learning
framework for tackling machine learning competitions. This framework has been
learned by us, validated and improved over a period of more than two years by
part... | 40 |
Learning and Generalisation of Primitives Skills Towards Robust Dual-arm Manipulation | Robots are becoming a vital ingredient in society. Some of their daily tasks
require dual-arm manipulation skills in the rapidly changing, dynamic and
unpredictable real-world environments where they have to operate. Given the
expertise of humans in conducting these activities, it is natural to study
humans' motions to... | Liked | jechoi@andrew.cmu.edu | Learning and Generalisation of Primitives Skills Towards Robust Dual-arm Manipulation : Robots are becoming a vital ingredient in society. Some of their daily tasks
require dual-arm manipulation skills in the rapidly changing, dynamic and
unpredictable real-world environments where they have to operate. Given the
exper... | 1 | jechoi@andrew.cmu.edu [SEP] Learning and Generalisation of Primitives Skills Towards Robust Dual-arm Manipulation : Robots are becoming a vital ingredient in society. Some of their daily tasks
require dual-arm manipulation skills in the rapidly changing, dynamic and
unpredictable real-world environments where they have... | 538 |
Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality | Deep learning has shown high performances in various types of tasks from
visual recognition to natural language processing, which indicates superior
flexibility and adaptivity of deep learning. To understand this phenomenon
theoretically, we develop a new approximation and estimation error analysis of
deep learning wit... | Disliked | zrz@andrew.cmu.edu | Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality : Deep learning has shown high performances in various types of tasks from
visual recognition to natural language processing, which indicates superior
flexibility and adaptivity of deep learning... | 0 | zrz@andrew.cmu.edu [SEP] Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality : Deep learning has shown high performances in various types of tasks from
visual recognition to natural language processing, which indicates superior
flexibility and ad... | 226 |
Perception Imitation: Towards Synthesis-free Simulator for Autonomous Vehicles | We propose a perception imitation method to simulate results of a certain
perception model, and discuss a new heuristic route of autonomous driving
simulator without data synthesis. The motivation is that original sensor data
is not always necessary for tasks such as planning and control when semantic
perception result... | Liked | zrz@andrew.cmu.edu | Perception Imitation: Towards Synthesis-free Simulator for Autonomous Vehicles : We propose a perception imitation method to simulate results of a certain
perception model, and discuss a new heuristic route of autonomous driving
simulator without data synthesis. The motivation is that original sensor data
is not always... | 1 | zrz@andrew.cmu.edu [SEP] Perception Imitation: Towards Synthesis-free Simulator for Autonomous Vehicles : We propose a perception imitation method to simulate results of a certain
perception model, and discuss a new heuristic route of autonomous driving
simulator without data synthesis. The motivation is that original ... | 331 |
Situated Cameras, Situated Knowledges: Towards an Egocentric Epistemology for Computer Vision | In her influential 1988 paper, Situated Knowledges, Donna Haraway uses vision
and perspective as a metaphor to discuss scientific knowledge. Today,
egocentric computer vision discusses many of the same issues, except in a
literal vision context. In this short position paper, we collapse that
metaphor, and explore the i... | Disliked | zrz@andrew.cmu.edu | Situated Cameras, Situated Knowledges: Towards an Egocentric Epistemology for Computer Vision : In her influential 1988 paper, Situated Knowledges, Donna Haraway uses vision
and perspective as a metaphor to discuss scientific knowledge. Today,
egocentric computer vision discusses many of the same issues, except in a
li... | 0 | zrz@andrew.cmu.edu [SEP] Situated Cameras, Situated Knowledges: Towards an Egocentric Epistemology for Computer Vision : In her influential 1988 paper, Situated Knowledges, Donna Haraway uses vision
and perspective as a metaphor to discuss scientific knowledge. Today,
egocentric computer vision discusses many of the sa... | 382 |
Robot Vision Architecture for Autonomous Clothes Manipulation | This paper presents a novel robot vision architecture for perceiving generic
3D clothes configurations. Our architecture is hierarchically structured,
starting from low-level curvatures, across mid-level geometric shapes \&
topology descriptions; and finally approaching high-level semantic surface
structure description... | Liked | jechoi@andrew.cmu.edu | Robot Vision Architecture for Autonomous Clothes Manipulation : This paper presents a novel robot vision architecture for perceiving generic
3D clothes configurations. Our architecture is hierarchically structured,
starting from low-level curvatures, across mid-level geometric shapes \&
topology descriptions; and final... | 1 | jechoi@andrew.cmu.edu [SEP] Robot Vision Architecture for Autonomous Clothes Manipulation : This paper presents a novel robot vision architecture for perceiving generic
3D clothes configurations. Our architecture is hierarchically structured,
starting from low-level curvatures, across mid-level geometric shapes \&
topo... | 462 |
Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey | Deep reinforcement learning augments the reinforcement learning framework and
utilizes the powerful representation of deep neural networks. Recent works have
demonstrated the remarkable successes of deep reinforcement learning in various
domains including finance, medicine, healthcare, video games, robotics, and
comput... | Liked | zrz@andrew.cmu.edu | Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey : Deep reinforcement learning augments the reinforcement learning framework and
utilizes the powerful representation of deep neural networks. Recent works have
demonstrated the remarkable successes of deep reinforcement learning in various
domains i... | 1 | zrz@andrew.cmu.edu [SEP] Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey : Deep reinforcement learning augments the reinforcement learning framework and
utilizes the powerful representation of deep neural networks. Recent works have
demonstrated the remarkable successes of deep reinforcement lear... | 168 |
Applying Machine Learning to Life Insurance: some knowledge sharing to master it | Machine Learning permeates many industries, which brings new source of
benefits for companies. However within the life insurance industry, Machine
Learning is not widely used in practice as over the past years statistical
models have shown their efficiency for risk assessment. Thus insurers may face
difficulties to ass... | Disliked | zrz@andrew.cmu.edu | Applying Machine Learning to Life Insurance: some knowledge sharing to master it : Machine Learning permeates many industries, which brings new source of
benefits for companies. However within the life insurance industry, Machine
Learning is not widely used in practice as over the past years statistical
models have sho... | 0 | zrz@andrew.cmu.edu [SEP] Applying Machine Learning to Life Insurance: some knowledge sharing to master it : Machine Learning permeates many industries, which brings new source of
benefits for companies. However within the life insurance industry, Machine
Learning is not widely used in practice as over the past years st... | 112 |
Deep Active Learning by Leveraging Training Dynamics | Active learning theories and methods have been extensively studied in
classical statistical learning settings. However, deep active learning, i.e.,
active learning with deep learning models, is usually based on empirical
criteria without solid theoretical justification, thus suffering from heavy
doubts when some of tho... | Liked | zrz@andrew.cmu.edu | Deep Active Learning by Leveraging Training Dynamics : Active learning theories and methods have been extensively studied in
classical statistical learning settings. However, deep active learning, i.e.,
active learning with deep learning models, is usually based on empirical
criteria without solid theoretical justifica... | 1 | zrz@andrew.cmu.edu [SEP] Deep Active Learning by Leveraging Training Dynamics : Active learning theories and methods have been extensively studied in
classical statistical learning settings. However, deep active learning, i.e.,
active learning with deep learning models, is usually based on empirical
criteria without so... | 225 |
Opening the black box of deep learning | The great success of deep learning shows that its technology contains
profound truth, and understanding its internal mechanism not only has important
implications for the development of its technology and effective application in
various fields, but also provides meaningful insights into the understanding of
human brai... | Disliked | zrz@andrew.cmu.edu | Opening the black box of deep learning : The great success of deep learning shows that its technology contains
profound truth, and understanding its internal mechanism not only has important
implications for the development of its technology and effective application in
various fields, but also provides meaningful insi... | 0 | zrz@andrew.cmu.edu [SEP] Opening the black box of deep learning : The great success of deep learning shows that its technology contains
profound truth, and understanding its internal mechanism not only has important
implications for the development of its technology and effective application in
various fields, but also... | 158 |
Are object detection assessment criteria ready for maritime computer vision? | Maritime vessels equipped with visible and infrared cameras can complement
other conventional sensors for object detection. However, application of
computer vision techniques in maritime domain received attention only recently.
The maritime environment offers its own unique requirements and challenges.
Assessment of th... | Liked | zrz@andrew.cmu.edu | Are object detection assessment criteria ready for maritime computer vision? : Maritime vessels equipped with visible and infrared cameras can complement
other conventional sensors for object detection. However, application of
computer vision techniques in maritime domain received attention only recently.
The maritime ... | 1 | zrz@andrew.cmu.edu [SEP] Are object detection assessment criteria ready for maritime computer vision? : Maritime vessels equipped with visible and infrared cameras can complement
other conventional sensors for object detection. However, application of
computer vision techniques in maritime domain received attention onl... | 338 |
Uncertainty-Aware Perception-Based Control for Autonomous Racing | Autonomous systems operating in unknown environments often rely heavily on
visual sensor data, yet making safe and informed control decisions based on
these measurements remains a significant challenge. To facilitate the
integration of perception and control in autonomous vehicles, we propose a
novel perception-based c... | Liked | zrz@andrew.cmu.edu | Uncertainty-Aware Perception-Based Control for Autonomous Racing : Autonomous systems operating in unknown environments often rely heavily on
visual sensor data, yet making safe and informed control decisions based on
these measurements remains a significant challenge. To facilitate the
integration of perception and co... | 1 | zrz@andrew.cmu.edu [SEP] Uncertainty-Aware Perception-Based Control for Autonomous Racing : Autonomous systems operating in unknown environments often rely heavily on
visual sensor data, yet making safe and informed control decisions based on
these measurements remains a significant challenge. To facilitate the
integra... | 326 |
Semi-supervised Learning on Large Graphs: is Poisson Learning a Game-Changer? | We explain Poisson learning on graph-based semi-supervised learning to see if
it could avoid the problem of global information loss problem as Laplace-based
learning methods on large graphs. From our analysis, Poisson learning is simply
Laplace regularization with thresholding, cannot overcome the problem. | Disliked | zrz@andrew.cmu.edu | Semi-supervised Learning on Large Graphs: is Poisson Learning a Game-Changer? : We explain Poisson learning on graph-based semi-supervised learning to see if
it could avoid the problem of global information loss problem as Laplace-based
learning methods on large graphs. From our analysis, Poisson learning is simply
Lap... | 0 | zrz@andrew.cmu.edu [SEP] Semi-supervised Learning on Large Graphs: is Poisson Learning a Game-Changer? : We explain Poisson learning on graph-based semi-supervised learning to see if
it could avoid the problem of global information loss problem as Laplace-based
learning methods on large graphs. From our analysis, Poiss... | 141 |
Human-Robot Collaboration for the Remote Control of Mobile Humanoid Robots with Torso-Arm Coordination | Recently, many humanoid robots have been increasingly deployed in various
facilities, including hospitals and assisted living environments, where they
are often remotely controlled by human operators. Their kinematic redundancy
enhances reachability and manipulability, enabling them to navigate complex,
cluttered envir... | Liked | jechoi@andrew.cmu.edu | Human-Robot Collaboration for the Remote Control of Mobile Humanoid Robots with Torso-Arm Coordination : Recently, many humanoid robots have been increasingly deployed in various
facilities, including hospitals and assisted living environments, where they
are often remotely controlled by human operators. Their kinemati... | 1 | jechoi@andrew.cmu.edu [SEP] Human-Robot Collaboration for the Remote Control of Mobile Humanoid Robots with Torso-Arm Coordination : Recently, many humanoid robots have been increasingly deployed in various
facilities, including hospitals and assisted living environments, where they
are often remotely controlled by hum... | 453 |
Deep Learning: A Critical Appraisal | Although deep learning has historical roots going back decades, neither the
term "deep learning" nor the approach was popular just over five years ago,
when the field was reignited by papers such as Krizhevsky, Sutskever and
Hinton's now classic (2012) deep network model of Imagenet. What has the field
discovered in th... | Liked | zrz@andrew.cmu.edu | Deep Learning: A Critical Appraisal : Although deep learning has historical roots going back decades, neither the
term "deep learning" nor the approach was popular just over five years ago,
when the field was reignited by papers such as Krizhevsky, Sutskever and
Hinton's now classic (2012) deep network model of Imagene... | 1 | zrz@andrew.cmu.edu [SEP] Deep Learning: A Critical Appraisal : Although deep learning has historical roots going back decades, neither the
term "deep learning" nor the approach was popular just over five years ago,
when the field was reignited by papers such as Krizhevsky, Sutskever and
Hinton's now classic (2012) deep... | 180 |
Low-Shot Classification: A Comparison of Classical and Deep Transfer Machine Learning Approaches | Despite the recent success of deep transfer learning approaches in NLP, there
is a lack of quantitative studies demonstrating the gains these models offer in
low-shot text classification tasks over existing paradigms. Deep transfer
learning approaches such as BERT and ULMFiT demonstrate that they can beat
state-of-the-... | Disliked | zrz@andrew.cmu.edu | Low-Shot Classification: A Comparison of Classical and Deep Transfer Machine Learning Approaches : Despite the recent success of deep transfer learning approaches in NLP, there
is a lack of quantitative studies demonstrating the gains these models offer in
low-shot text classification tasks over existing paradigms. Dee... | 0 | zrz@andrew.cmu.edu [SEP] Low-Shot Classification: A Comparison of Classical and Deep Transfer Machine Learning Approaches : Despite the recent success of deep transfer learning approaches in NLP, there
is a lack of quantitative studies demonstrating the gains these models offer in
low-shot text classification tasks ove... | 269 |
Scenario-based Compositional Verification of Autonomous Systems with Neural Perception | Recent advances in deep learning have enabled the development of autonomous
systems that use deep neural networks for perception. Formal verification of
these systems is challenging due to the size and complexity of the perception
DNNs as well as hard-to-quantify, changing environment conditions. To address
these chall... | Disliked | zrz@andrew.cmu.edu | Scenario-based Compositional Verification of Autonomous Systems with Neural Perception : Recent advances in deep learning have enabled the development of autonomous
systems that use deep neural networks for perception. Formal verification of
these systems is challenging due to the size and complexity of the perception
... | 0 | zrz@andrew.cmu.edu [SEP] Scenario-based Compositional Verification of Autonomous Systems with Neural Perception : Recent advances in deep learning have enabled the development of autonomous
systems that use deep neural networks for perception. Formal verification of
these systems is challenging due to the size and comp... | 281 |
RoboFiSense: Attention-Based Robotic Arm Activity Recognition with WiFi Sensing | Despite the current surge of interest in autonomous robotic systems, robot
activity recognition within restricted indoor environments remains a formidable
challenge. Conventional methods for detecting and recognizing robotic arms'
activities often rely on vision-based or light detection and ranging (LiDAR)
sensors, whi... | Liked | jechoi@andrew.cmu.edu | RoboFiSense: Attention-Based Robotic Arm Activity Recognition with WiFi Sensing : Despite the current surge of interest in autonomous robotic systems, robot
activity recognition within restricted indoor environments remains a formidable
challenge. Conventional methods for detecting and recognizing robotic arms'
activit... | 1 | jechoi@andrew.cmu.edu [SEP] RoboFiSense: Attention-Based Robotic Arm Activity Recognition with WiFi Sensing : Despite the current surge of interest in autonomous robotic systems, robot
activity recognition within restricted indoor environments remains a formidable
challenge. Conventional methods for detecting and recog... | 450 |
Panoptic Perception for Autonomous Driving: A Survey | Panoptic perception represents a forefront advancement in autonomous driving
technology, unifying multiple perception tasks into a singular, cohesive
framework to facilitate a thorough understanding of the vehicle's surroundings.
This survey reviews typical panoptic perception models for their unique inputs
and archite... | Liked | zrz@andrew.cmu.edu | Panoptic Perception for Autonomous Driving: A Survey : Panoptic perception represents a forefront advancement in autonomous driving
technology, unifying multiple perception tasks into a singular, cohesive
framework to facilitate a thorough understanding of the vehicle's surroundings.
This survey reviews typical panopti... | 1 | zrz@andrew.cmu.edu [SEP] Panoptic Perception for Autonomous Driving: A Survey : Panoptic perception represents a forefront advancement in autonomous driving
technology, unifying multiple perception tasks into a singular, cohesive
framework to facilitate a thorough understanding of the vehicle's surroundings.
This surve... | 270 |
Reinforcement Learning and Video Games | Reinforcement learning has exceeded human-level performance in game playing
AI with deep learning methods according to the experiments from DeepMind on Go
and Atari games. Deep learning solves high dimension input problems which stop
the development of reinforcement for many years. This study uses both two
techniques t... | Disliked | zrz@andrew.cmu.edu | Reinforcement Learning and Video Games : Reinforcement learning has exceeded human-level performance in game playing
AI with deep learning methods according to the experiments from DeepMind on Go
and Atari games. Deep learning solves high dimension input problems which stop
the development of reinforcement for many yea... | 0 | zrz@andrew.cmu.edu [SEP] Reinforcement Learning and Video Games : Reinforcement learning has exceeded human-level performance in game playing
AI with deep learning methods according to the experiments from DeepMind on Go
and Atari games. Deep learning solves high dimension input problems which stop
the development of r... | 256 |
Adapting Computer Vision Algorithms for Omnidirectional Video | Omnidirectional (360{\deg}) video has got quite popular because it provides a
highly immersive viewing experience. For computer vision algorithms, it poses
several challenges, like the special (equirectangular) projection commonly
employed and the huge image size. In this work, we give a high-level overview
of these ch... | Disliked | zrz@andrew.cmu.edu | Adapting Computer Vision Algorithms for Omnidirectional Video : Omnidirectional (360{\deg}) video has got quite popular because it provides a
highly immersive viewing experience. For computer vision algorithms, it poses
several challenges, like the special (equirectangular) projection commonly
employed and the huge ima... | 0 | zrz@andrew.cmu.edu [SEP] Adapting Computer Vision Algorithms for Omnidirectional Video : Omnidirectional (360{\deg}) video has got quite popular because it provides a
highly immersive viewing experience. For computer vision algorithms, it poses
several challenges, like the special (equirectangular) projection commonly
... | 345 |
Computers Should Be Uniters Not Dividers: A Vision of Computer-Enhanced Happy Future | This manifesto provides a vision of how computers can be used to bring people
together, to enhance people's use of their natural creativity, and thus, make
them happier. | Disliked | zrz@andrew.cmu.edu | Computers Should Be Uniters Not Dividers: A Vision of Computer-Enhanced Happy Future : This manifesto provides a vision of how computers can be used to bring people
together, to enhance people's use of their natural creativity, and thus, make
them happier. | 0 | zrz@andrew.cmu.edu [SEP] Computers Should Be Uniters Not Dividers: A Vision of Computer-Enhanced Happy Future : This manifesto provides a vision of how computers can be used to bring people
together, to enhance people's use of their natural creativity, and thus, make
them happier. | 374 |
A systematic review of fuzzing based on machine learning techniques | Security vulnerabilities play a vital role in network security system.
Fuzzing technology is widely used as a vulnerability discovery technology to
reduce damage in advance. However, traditional fuzzing techniques have many
challenges, such as how to mutate input seed files, how to increase code
coverage, and how to ef... | Disliked | zrz@andrew.cmu.edu | A systematic review of fuzzing based on machine learning techniques : Security vulnerabilities play a vital role in network security system.
Fuzzing technology is widely used as a vulnerability discovery technology to
reduce damage in advance. However, traditional fuzzing techniques have many
challenges, such as how to... | 0 | zrz@andrew.cmu.edu [SEP] A systematic review of fuzzing based on machine learning techniques : Security vulnerabilities play a vital role in network security system.
Fuzzing technology is widely used as a vulnerability discovery technology to
reduce damage in advance. However, traditional fuzzing techniques have many
c... | 127 |
Machine learning and domain decomposition methods -- a survey | Hybrid algorithms, which combine black-box machine learning methods with
experience from traditional numerical methods and domain expertise from diverse
application areas, are progressively gaining importance in scientific machine
learning and various industrial domains, especially in computational science
and engineer... | Liked | zrz@andrew.cmu.edu | Machine learning and domain decomposition methods -- a survey : Hybrid algorithms, which combine black-box machine learning methods with
experience from traditional numerical methods and domain expertise from diverse
application areas, are progressively gaining importance in scientific machine
learning and various indu... | 1 | zrz@andrew.cmu.edu [SEP] Machine learning and domain decomposition methods -- a survey : Hybrid algorithms, which combine black-box machine learning methods with
experience from traditional numerical methods and domain expertise from diverse
application areas, are progressively gaining importance in scientific machine
... | 114 |
Category Theory in Machine Learning | Over the past two decades machine learning has permeated almost every realm
of technology. At the same time, many researchers have begun using category
theory as a unifying language, facilitating communication between different
scientific disciplines. It is therefore unsurprising that there is a burgeoning
interest in ... | Disliked | zrz@andrew.cmu.edu | Category Theory in Machine Learning : Over the past two decades machine learning has permeated almost every realm
of technology. At the same time, many researchers have begun using category
theory as a unifying language, facilitating communication between different
scientific disciplines. It is therefore unsurprising t... | 0 | zrz@andrew.cmu.edu [SEP] Category Theory in Machine Learning : Over the past two decades machine learning has permeated almost every realm
of technology. At the same time, many researchers have begun using category
theory as a unifying language, facilitating communication between different
scientific disciplines. It is... | 89 |
SeePerSea: Multi-modal Perception Dataset of In-water Objects for Autonomous Surface Vehicles | This paper introduces the first publicly accessible labeled multi-modal
perception dataset for autonomous maritime navigation, focusing on in-water
obstacles within the aquatic environment to enhance situational awareness for
Autonomous Surface Vehicles (ASVs). This dataset, collected over 4 years and
consisting of div... | Liked | zrz@andrew.cmu.edu | SeePerSea: Multi-modal Perception Dataset of In-water Objects for Autonomous Surface Vehicles : This paper introduces the first publicly accessible labeled multi-modal
perception dataset for autonomous maritime navigation, focusing on in-water
obstacles within the aquatic environment to enhance situational awareness fo... | 1 | zrz@andrew.cmu.edu [SEP] SeePerSea: Multi-modal Perception Dataset of In-water Objects for Autonomous Surface Vehicles : This paper introduces the first publicly accessible labeled multi-modal
perception dataset for autonomous maritime navigation, focusing on in-water
obstacles within the aquatic environment to enhance... | 320 |
An Optimal Control View of Adversarial Machine Learning | I describe an optimal control view of adversarial machine learning, where the
dynamical system is the machine learner, the input are adversarial actions, and
the control costs are defined by the adversary's goals to do harm and be hard
to detect. This view encompasses many types of adversarial machine learning,
includi... | Disliked | zrz@andrew.cmu.edu | An Optimal Control View of Adversarial Machine Learning : I describe an optimal control view of adversarial machine learning, where the
dynamical system is the machine learner, the input are adversarial actions, and
the control costs are defined by the adversary's goals to do harm and be hard
to detect. This view encom... | 0 | zrz@andrew.cmu.edu [SEP] An Optimal Control View of Adversarial Machine Learning : I describe an optimal control view of adversarial machine learning, where the
dynamical system is the machine learner, the input are adversarial actions, and
the control costs are defined by the adversary's goals to do harm and be hard
t... | 3 |
In-Machine-Learning Database: Reimagining Deep Learning with Old-School SQL | In-database machine learning has been very popular, almost being a cliche.
However, can we do it the other way around? In this work, we say "yes" by
applying plain old SQL to deep learning, in a sense implementing deep learning
algorithms with SQL. Most deep learning frameworks, as well as generic machine
learning ones... | Disliked | zrz@andrew.cmu.edu | In-Machine-Learning Database: Reimagining Deep Learning with Old-School SQL : In-database machine learning has been very popular, almost being a cliche.
However, can we do it the other way around? In this work, we say "yes" by
applying plain old SQL to deep learning, in a sense implementing deep learning
algorithms wit... | 0 | zrz@andrew.cmu.edu [SEP] In-Machine-Learning Database: Reimagining Deep Learning with Old-School SQL : In-database machine learning has been very popular, almost being a cliche.
However, can we do it the other way around? In this work, we say "yes" by
applying plain old SQL to deep learning, in a sense implementing dee... | 94 |
Defensive Perception: Estimation and Monitoring of Neural Network Performance under Deployment | In this paper, we propose a method for addressing the issue of unnoticed
catastrophic deployment and domain shift in neural networks for semantic
segmentation in autonomous driving. Our approach is based on the idea that deep
learning-based perception for autonomous driving is uncertain and best
represented as a probab... | Liked | zrz@andrew.cmu.edu | Defensive Perception: Estimation and Monitoring of Neural Network Performance under Deployment : In this paper, we propose a method for addressing the issue of unnoticed
catastrophic deployment and domain shift in neural networks for semantic
segmentation in autonomous driving. Our approach is based on the idea that de... | 1 | zrz@andrew.cmu.edu [SEP] Defensive Perception: Estimation and Monitoring of Neural Network Performance under Deployment : In this paper, we propose a method for addressing the issue of unnoticed
catastrophic deployment and domain shift in neural networks for semantic
segmentation in autonomous driving. Our approach is ... | 312 |
The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning | With the advance of the powerful heterogeneous, parallel and distributed
computing systems and ever increasing immense amount of data, machine learning
has become an indispensable part of cutting-edge technology, scientific
research and consumer products. In this study, we present a review of modern
machine and deep le... | Liked | zrz@andrew.cmu.edu | The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning : With the advance of the powerful heterogeneous, parallel and distributed
computing systems and ever increasing immense amount of data, machine learning
has become an indispensable part of cutting-edge technology, scienti... | 1 | zrz@andrew.cmu.edu [SEP] The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning : With the advance of the powerful heterogeneous, parallel and distributed
computing systems and ever increasing immense amount of data, machine learning
has become an indispensable part of cutting... | 38 |
Redundant Perception and State Estimation for Reliable Autonomous Racing | In autonomous racing, vehicles operate close to the limits of handling and a
sensor failure can have critical consequences. To limit the impact of such
failures, this paper presents the redundant perception and state estimation
approaches developed for an autonomous race car. Redundancy in perception is
achieved by est... | Disliked | zrz@andrew.cmu.edu | Redundant Perception and State Estimation for Reliable Autonomous Racing : In autonomous racing, vehicles operate close to the limits of handling and a
sensor failure can have critical consequences. To limit the impact of such
failures, this paper presents the redundant perception and state estimation
approaches develo... | 0 | zrz@andrew.cmu.edu [SEP] Redundant Perception and State Estimation for Reliable Autonomous Racing : In autonomous racing, vehicles operate close to the limits of handling and a
sensor failure can have critical consequences. To limit the impact of such
failures, this paper presents the redundant perception and state est... | 322 |
G.O.G: A Versatile Gripper-On-Gripper Design for Bimanual Cloth Manipulation with a Single Robotic Arm | The manipulation of garments poses research challenges due to their
deformable nature and the extensive variability in shapes and sizes. Despite
numerous attempts by researchers to address these via approaches involving
robot perception and control, there has been a relatively limited interest in
resolving it through t... | Liked | jechoi@andrew.cmu.edu | G.O.G: A Versatile Gripper-On-Gripper Design for Bimanual Cloth Manipulation with a Single Robotic Arm : The manipulation of garments poses research challenges due to their
deformable nature and the extensive variability in shapes and sizes. Despite
numerous attempts by researchers to address these via approaches invol... | 1 | jechoi@andrew.cmu.edu [SEP] G.O.G: A Versatile Gripper-On-Gripper Design for Bimanual Cloth Manipulation with a Single Robotic Arm : The manipulation of garments poses research challenges due to their
deformable nature and the extensive variability in shapes and sizes. Despite
numerous attempts by researchers to addres... | 419 |
UMArm: Untethered, Modular, Wearable, Soft Pneumatic Arm | Robotic arms are essential to modern industries, however, their adaptability
to unstructured environments remains limited. Soft robotic arms, particularly
those actuated pneumatically, offer greater adaptability in unstructured
environments and enhanced safety for human-robot interaction. However, current
pneumatic sof... | Liked | jechoi@andrew.cmu.edu | UMArm: Untethered, Modular, Wearable, Soft Pneumatic Arm : Robotic arms are essential to modern industries, however, their adaptability
to unstructured environments remains limited. Soft robotic arms, particularly
those actuated pneumatically, offer greater adaptability in unstructured
environments and enhanced safety ... | 1 | jechoi@andrew.cmu.edu [SEP] UMArm: Untethered, Modular, Wearable, Soft Pneumatic Arm : Robotic arms are essential to modern industries, however, their adaptability
to unstructured environments remains limited. Soft robotic arms, particularly
those actuated pneumatically, offer greater adaptability in unstructured
envir... | 412 |
Toward a Universal Concept of Artificial Personality: Implementing Robotic Personality in a Kinova Arm | The fundamental role of personality in shaping interactions is increasingly
being exploited in robotics. A carefully designed robotic personality has been
shown to improve several key aspects of Human-Robot Interaction (HRI). However,
the fragmentation and rigidity of existing approaches reveal even greater
challenges ... | Liked | jechoi@andrew.cmu.edu | Toward a Universal Concept of Artificial Personality: Implementing Robotic Personality in a Kinova Arm : The fundamental role of personality in shaping interactions is increasingly
being exploited in robotics. A carefully designed robotic personality has been
shown to improve several key aspects of Human-Robot Interact... | 1 | jechoi@andrew.cmu.edu [SEP] Toward a Universal Concept of Artificial Personality: Implementing Robotic Personality in a Kinova Arm : The fundamental role of personality in shaping interactions is increasingly
being exploited in robotics. A carefully designed robotic personality has been
shown to improve several key asp... | 503 |
DeepSI: Interactive Deep Learning for Semantic Interaction | In this paper, we design novel interactive deep learning methods to improve
semantic interactions in visual analytics applications. The ability of semantic
interaction to infer analysts' precise intents during sensemaking is dependent
on the quality of the underlying data representation. We propose the
$\text{DeepSI}_{... | Disliked | zrz@andrew.cmu.edu | DeepSI: Interactive Deep Learning for Semantic Interaction : In this paper, we design novel interactive deep learning methods to improve
semantic interactions in visual analytics applications. The ability of semantic
interaction to infer analysts' precise intents during sensemaking is dependent
on the quality of the un... | 0 | zrz@andrew.cmu.edu [SEP] DeepSI: Interactive Deep Learning for Semantic Interaction : In this paper, we design novel interactive deep learning methods to improve
semantic interactions in visual analytics applications. The ability of semantic
interaction to infer analysts' precise intents during sensemaking is dependent... | 232 |
Assisting MoCap-Based Teleoperation of Robot Arm using Augmented Reality Visualisations | Teleoperating a robot arm involves the human operator positioning the robot's
end-effector or programming each joint. Whereas humans can control their own
arms easily by integrating visual and proprioceptive feedback, it is
challenging to control an external robot arm in the same way, due to its
inconsistent orientatio... | Liked | jechoi@andrew.cmu.edu | Assisting MoCap-Based Teleoperation of Robot Arm using Augmented Reality Visualisations : Teleoperating a robot arm involves the human operator positioning the robot's
end-effector or programming each joint. Whereas humans can control their own
arms easily by integrating visual and proprioceptive feedback, it is
challe... | 1 | jechoi@andrew.cmu.edu [SEP] Assisting MoCap-Based Teleoperation of Robot Arm using Augmented Reality Visualisations : Teleoperating a robot arm involves the human operator positioning the robot's
end-effector or programming each joint. Whereas humans can control their own
arms easily by integrating visual and proprioce... | 392 |
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