Title string | Abstract string | Status string | User string | text string | label int64 | combined_text string | __index_level_0__ int64 |
|---|---|---|---|---|---|---|---|
Temporal-related Convolutional-Restricted-Boltzmann-Machine capable of learning relational order via reinforcement learning procedure? | In this article, we extend the conventional framework of
convolutional-Restricted-Boltzmann-Machine to learn highly abstract features
among abitrary number of time related input maps by constructing a layer of
multiplicative units, which capture the relations among inputs. In many cases,
more than two maps are strongly... | Disliked | zrz@andrew.cmu.edu | Temporal-related Convolutional-Restricted-Boltzmann-Machine capable of learning relational order via reinforcement learning procedure? : In this article, we extend the conventional framework of
convolutional-Restricted-Boltzmann-Machine to learn highly abstract features
among abitrary number of time related input maps ... | 0 | zrz@andrew.cmu.edu [SEP] Temporal-related Convolutional-Restricted-Boltzmann-Machine capable of learning relational order via reinforcement learning procedure? : In this article, we extend the conventional framework of
convolutional-Restricted-Boltzmann-Machine to learn highly abstract features
among abitrary number of... | 56 |
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey | Since the 2004 DARPA Grand Challenge, the autonomous driving technology has
witnessed nearly two decades of rapid development. Particularly, in recent
years, with the application of new sensors and deep learning technologies
extending to the autonomous field, the development of autonomous driving
technology has continu... | Liked | zrz@andrew.cmu.edu | Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey : Since the 2004 DARPA Grand Challenge, the autonomous driving technology has
witnessed nearly two decades of rapid development. Particularly, in recent
years, with the application of new sensors and deep learning technologies
extending ... | 1 | zrz@andrew.cmu.edu [SEP] Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey : Since the 2004 DARPA Grand Challenge, the autonomous driving technology has
witnessed nearly two decades of rapid development. Particularly, in recent
years, with the application of new sensors and deep learnin... | 223 |
UniDiffGrasp: A Unified Framework Integrating VLM Reasoning and VLM-Guided Part Diffusion for Open-Vocabulary Constrained Grasping with Dual Arms | Open-vocabulary, task-oriented grasping of specific functional parts,
particularly with dual arms, remains a key challenge, as current
Vision-Language Models (VLMs), while enhancing task understanding, often
struggle with precise grasp generation within defined constraints and effective
dual-arm coordination. We innova... | Liked | jechoi@andrew.cmu.edu | UniDiffGrasp: A Unified Framework Integrating VLM Reasoning and VLM-Guided Part Diffusion for Open-Vocabulary Constrained Grasping with Dual Arms : Open-vocabulary, task-oriented grasping of specific functional parts,
particularly with dual arms, remains a key challenge, as current
Vision-Language Models (VLMs), while ... | 1 | jechoi@andrew.cmu.edu [SEP] UniDiffGrasp: A Unified Framework Integrating VLM Reasoning and VLM-Guided Part Diffusion for Open-Vocabulary Constrained Grasping with Dual Arms : Open-vocabulary, task-oriented grasping of specific functional parts,
particularly with dual arms, remains a key challenge, as current
Vision-La... | 559 |
Design and Development of a Remotely Wire-Driven Walking Robot | Operating in environments too harsh or inaccessible for humans is one of the
critical roles expected of robots. However, such environments often pose risks
to electronic components as well. To overcome this, various approaches have
been developed, including autonomous mobile robots without electronics,
hydraulic remote... | Liked | jechoi@andrew.cmu.edu | Design and Development of a Remotely Wire-Driven Walking Robot : Operating in environments too harsh or inaccessible for humans is one of the
critical roles expected of robots. However, such environments often pose risks
to electronic components as well. To overcome this, various approaches have
been developed, includi... | 1 | jechoi@andrew.cmu.edu [SEP] Design and Development of a Remotely Wire-Driven Walking Robot : Operating in environments too harsh or inaccessible for humans is one of the
critical roles expected of robots. However, such environments often pose risks
to electronic components as well. To overcome this, various approaches ... | 19 |
Knowledge-augmented Column Networks: Guiding Deep Learning with Advice | Recently, deep models have had considerable success in several tasks,
especially with low-level representations. However, effective learning from
sparse noisy samples is a major challenge in most deep models, especially in
domains with structured representations. Inspired by the proven success of
human guided machine l... | Disliked | zrz@andrew.cmu.edu | Knowledge-augmented Column Networks: Guiding Deep Learning with Advice : Recently, deep models have had considerable success in several tasks,
especially with low-level representations. However, effective learning from
sparse noisy samples is a major challenge in most deep models, especially in
domains with structured ... | 0 | zrz@andrew.cmu.edu [SEP] Knowledge-augmented Column Networks: Guiding Deep Learning with Advice : Recently, deep models have had considerable success in several tasks,
especially with low-level representations. However, effective learning from
sparse noisy samples is a major challenge in most deep models, especially in... | 255 |
Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge | Medical vision-and-language pre-training (Med-VLP) has received considerable
attention owing to its applicability to extracting generic vision-and-language
representations from medical images and texts. Most existing methods mainly
contain three elements: uni-modal encoders (i.e., a vision encoder and a
language encode... | Liked | zrz@andrew.cmu.edu | Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge : Medical vision-and-language pre-training (Med-VLP) has received considerable
attention owing to its applicability to extracting generic vision-and-language
representations from medical images and texts. Most existing methods ma... | 1 | zrz@andrew.cmu.edu [SEP] Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge : Medical vision-and-language pre-training (Med-VLP) has received considerable
attention owing to its applicability to extracting generic vision-and-language
representations from medical images and texts.... | 349 |
Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement | We investigate the problem of coordinating two robot arms to solve
non-monotone tabletop multi-object rearrangement tasks. In a non-monotone
rearrangement task, complex object-object dependencies exist that require
moving some objects multiple times to solve an instance. In working with two
arms in a large workspace, s... | Liked | jechoi@andrew.cmu.edu | Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement : We investigate the problem of coordinating two robot arms to solve
non-monotone tabletop multi-object rearrangement tasks. In a non-monotone
rearrangement task, complex object-object dependencies exist that require
moving some objects multiple ... | 1 | jechoi@andrew.cmu.edu [SEP] Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement : We investigate the problem of coordinating two robot arms to solve
non-monotone tabletop multi-object rearrangement tasks. In a non-monotone
rearrangement task, complex object-object dependencies exist that require
m... | 21 |
Deep Learning of Representations: Looking Forward | Deep learning research aims at discovering learning algorithms that discover
multiple levels of distributed representations, with higher levels representing
more abstract concepts. Although the study of deep learning has already led to
impressive theoretical results, learning algorithms and breakthrough
experiments, se... | Liked | zrz@andrew.cmu.edu | Deep Learning of Representations: Looking Forward : Deep learning research aims at discovering learning algorithms that discover
multiple levels of distributed representations, with higher levels representing
more abstract concepts. Although the study of deep learning has already led to
impressive theoretical results, ... | 1 | zrz@andrew.cmu.edu [SEP] Deep Learning of Representations: Looking Forward : Deep learning research aims at discovering learning algorithms that discover
multiple levels of distributed representations, with higher levels representing
more abstract concepts. Although the study of deep learning has already led to
impress... | 252 |
Situation-aware Autonomous Driving Decision Making with Cooperative Perception on Demand | This paper investigates the impact of cooperative perception on autonomous
driving decision making on urban roads. The extended perception range
contributed by the cooperative perception can be properly leveraged to address
the implicit dependencies within the vehicles, thereby the vehicle decision
making performance c... | Disliked | zrz@andrew.cmu.edu | Situation-aware Autonomous Driving Decision Making with Cooperative Perception on Demand : This paper investigates the impact of cooperative perception on autonomous
driving decision making on urban roads. The extended perception range
contributed by the cooperative perception can be properly leveraged to address
the i... | 0 | zrz@andrew.cmu.edu [SEP] Situation-aware Autonomous Driving Decision Making with Cooperative Perception on Demand : This paper investigates the impact of cooperative perception on autonomous
driving decision making on urban roads. The extended perception range
contributed by the cooperative perception can be properly l... | 274 |
PSL is Dead. Long Live PSL | Property Specification Language (PSL) is a form of temporal logic that has
been mainly used in discrete domains (e.g. formal hardware verification). In
this paper, we show that by merging machine learning techniques with PSL
monitors, we can extend PSL to work on continuous domains. We apply this
technique in machine l... | Disliked | zrz@andrew.cmu.edu | PSL is Dead. Long Live PSL : Property Specification Language (PSL) is a form of temporal logic that has
been mainly used in discrete domains (e.g. formal hardware verification). In
this paper, we show that by merging machine learning techniques with PSL
monitors, we can extend PSL to work on continuous domains. We appl... | 0 | zrz@andrew.cmu.edu [SEP] PSL is Dead. Long Live PSL : Property Specification Language (PSL) is a form of temporal logic that has
been mainly used in discrete domains (e.g. formal hardware verification). In
this paper, we show that by merging machine learning techniques with PSL
monitors, we can extend PSL to work on co... | 147 |
Joint Training of Deep Boltzmann Machines | We introduce a new method for training deep Boltzmann machines jointly. Prior
methods require an initial learning pass that trains the deep Boltzmann machine
greedily, one layer at a time, or do not perform well on classifi- cation
tasks. | Disliked | zrz@andrew.cmu.edu | Joint Training of Deep Boltzmann Machines : We introduce a new method for training deep Boltzmann machines jointly. Prior
methods require an initial learning pass that trains the deep Boltzmann machine
greedily, one layer at a time, or do not perform well on classifi- cation
tasks. | 0 | zrz@andrew.cmu.edu [SEP] Joint Training of Deep Boltzmann Machines : We introduce a new method for training deep Boltzmann machines jointly. Prior
methods require an initial learning pass that trains the deep Boltzmann machine
greedily, one layer at a time, or do not perform well on classifi- cation
tasks. | 41 |
Optimal Scheduling of a Dual-Arm Robot for Efficient Strawberry Harvesting in Plant Factories | Plant factory cultivation is widely recognized for its ability to optimize
resource use and boost crop yields. To further increase the efficiency in these
environments, we propose a mixed-integer linear programming (MILP) framework
that systematically schedules and coordinates dual-arm harvesting tasks,
minimizing the ... | Liked | jechoi@andrew.cmu.edu | Optimal Scheduling of a Dual-Arm Robot for Efficient Strawberry Harvesting in Plant Factories : Plant factory cultivation is widely recognized for its ability to optimize
resource use and boost crop yields. To further increase the efficiency in these
environments, we propose a mixed-integer linear programming (MILP) fr... | 1 | jechoi@andrew.cmu.edu [SEP] Optimal Scheduling of a Dual-Arm Robot for Efficient Strawberry Harvesting in Plant Factories : Plant factory cultivation is widely recognized for its ability to optimize
resource use and boost crop yields. To further increase the efficiency in these
environments, we propose a mixed-integer ... | 476 |
Inspiring Computer Vision System Solutions | The "digital Michelangelo project" was a seminal computer vision project in
the early 2000's that pushed the capabilities of acquisition systems and
involved multiple people from diverse fields, many of whom are now leaders in
industry and academia. Reviewing this project with modern eyes provides us with
the opportuni... | Disliked | zrz@andrew.cmu.edu | Inspiring Computer Vision System Solutions : The "digital Michelangelo project" was a seminal computer vision project in
the early 2000's that pushed the capabilities of acquisition systems and
involved multiple people from diverse fields, many of whom are now leaders in
industry and academia. Reviewing this project wi... | 0 | zrz@andrew.cmu.edu [SEP] Inspiring Computer Vision System Solutions : The "digital Michelangelo project" was a seminal computer vision project in
the early 2000's that pushed the capabilities of acquisition systems and
involved multiple people from diverse fields, many of whom are now leaders in
industry and academia. ... | 355 |
Modeling Generalization in Machine Learning: A Methodological and Computational Study | As machine learning becomes more and more available to the general public,
theoretical questions are turning into pressing practical issues. Possibly, one
of the most relevant concerns is the assessment of our confidence in trusting
machine learning predictions. In many real-world cases, it is of utmost
importance to e... | Disliked | zrz@andrew.cmu.edu | Modeling Generalization in Machine Learning: A Methodological and Computational Study : As machine learning becomes more and more available to the general public,
theoretical questions are turning into pressing practical issues. Possibly, one
of the most relevant concerns is the assessment of our confidence in trusting... | 0 | zrz@andrew.cmu.edu [SEP] Modeling Generalization in Machine Learning: A Methodological and Computational Study : As machine learning becomes more and more available to the general public,
theoretical questions are turning into pressing practical issues. Possibly, one
of the most relevant concerns is the assessment of o... | 117 |
Development of a Tendon Driven Variable Stiffness Continuum Robot with Layer Jamming | The purpose of this research is to design, fabricate and test a tendon driven
a continuum soft robot with three modular segments, each of which has a tunable
stiffness enabled by layer jamming technology. Compared with previous studies,
the robotic arm design of this project has a modular structure, which means the
len... | Liked | jechoi@andrew.cmu.edu | Development of a Tendon Driven Variable Stiffness Continuum Robot with Layer Jamming : The purpose of this research is to design, fabricate and test a tendon driven
a continuum soft robot with three modular segments, each of which has a tunable
stiffness enabled by layer jamming technology. Compared with previous studi... | 1 | jechoi@andrew.cmu.edu [SEP] Development of a Tendon Driven Variable Stiffness Continuum Robot with Layer Jamming : The purpose of this research is to design, fabricate and test a tendon driven
a continuum soft robot with three modular segments, each of which has a tunable
stiffness enabled by layer jamming technology. ... | 389 |
Lecture Notes: Optimization for Machine Learning | Lecture notes on optimization for machine learning, derived from a course at
Princeton University and tutorials given in MLSS, Buenos Aires, as well as
Simons Foundation, Berkeley. | Liked | zrz@andrew.cmu.edu | Lecture Notes: Optimization for Machine Learning : Lecture notes on optimization for machine learning, derived from a course at
Princeton University and tutorials given in MLSS, Buenos Aires, as well as
Simons Foundation, Berkeley. | 1 | zrz@andrew.cmu.edu [SEP] Lecture Notes: Optimization for Machine Learning : Lecture notes on optimization for machine learning, derived from a course at
Princeton University and tutorials given in MLSS, Buenos Aires, as well as
Simons Foundation, Berkeley. | 0 |
Extremal Configuration of Robot Arms in Three Dimensions | We define a volume function for a robot arms in 3-dimensional Euclidean space
and give geometric conditions for its critical points. For 3-arms this volume
function is an exact topological Morse function on the 3-sphere. | Liked | jechoi@andrew.cmu.edu | Extremal Configuration of Robot Arms in Three Dimensions : We define a volume function for a robot arms in 3-dimensional Euclidean space
and give geometric conditions for its critical points. For 3-arms this volume
function is an exact topological Morse function on the 3-sphere. | 1 | jechoi@andrew.cmu.edu [SEP] Extremal Configuration of Robot Arms in Three Dimensions : We define a volume function for a robot arms in 3-dimensional Euclidean space
and give geometric conditions for its critical points. For 3-arms this volume
function is an exact topological Morse function on the 3-sphere. | 546 |
Fairness in Deep Learning: A Computational Perspective | Deep learning is increasingly being used in high-stake decision making
applications that affect individual lives. However, deep learning models might
exhibit algorithmic discrimination behaviors with respect to protected groups,
potentially posing negative impacts on individuals and society. Therefore,
fairness in deep... | Liked | zrz@andrew.cmu.edu | Fairness in Deep Learning: A Computational Perspective : Deep learning is increasingly being used in high-stake decision making
applications that affect individual lives. However, deep learning models might
exhibit algorithmic discrimination behaviors with respect to protected groups,
potentially posing negative impact... | 1 | zrz@andrew.cmu.edu [SEP] Fairness in Deep Learning: A Computational Perspective : Deep learning is increasingly being used in high-stake decision making
applications that affect individual lives. However, deep learning models might
exhibit algorithmic discrimination behaviors with respect to protected groups,
potential... | 224 |
Intelligent Perception System for Vehicle-Road Cooperation | With the development of autonomous driving, the improvement of autonomous
driving technology for individual vehicles has reached the bottleneck. The
advancement of vehicle-road cooperation autonomous driving technology can
expand the vehicle's perception range, supplement the perception blind area and
improve the perce... | Liked | zrz@andrew.cmu.edu | Intelligent Perception System for Vehicle-Road Cooperation : With the development of autonomous driving, the improvement of autonomous
driving technology for individual vehicles has reached the bottleneck. The
advancement of vehicle-road cooperation autonomous driving technology can
expand the vehicle's perception rang... | 1 | zrz@andrew.cmu.edu [SEP] Intelligent Perception System for Vehicle-Road Cooperation : With the development of autonomous driving, the improvement of autonomous
driving technology for individual vehicles has reached the bottleneck. The
advancement of vehicle-road cooperation autonomous driving technology can
expand the ... | 288 |
Efficient Deep Feature Learning and Extraction via StochasticNets | Deep neural networks are a powerful tool for feature learning and extraction
given their ability to model high-level abstractions in highly complex data.
One area worth exploring in feature learning and extraction using deep neural
networks is efficient neural connectivity formation for faster feature learning
and extr... | Liked | zrz@andrew.cmu.edu | Efficient Deep Feature Learning and Extraction via StochasticNets : Deep neural networks are a powerful tool for feature learning and extraction
given their ability to model high-level abstractions in highly complex data.
One area worth exploring in feature learning and extraction using deep neural
networks is efficien... | 1 | zrz@andrew.cmu.edu [SEP] Efficient Deep Feature Learning and Extraction via StochasticNets : Deep neural networks are a powerful tool for feature learning and extraction
given their ability to model high-level abstractions in highly complex data.
One area worth exploring in feature learning and extraction using deep ne... | 210 |
Theoretical Models of Learning to Learn | A Machine can only learn if it is biased in some way. Typically the bias is
supplied by hand, for example through the choice of an appropriate set of
features. However, if the learning machine is embedded within an {\em
environment} of related tasks, then it can {\em learn} its own bias by learning
sufficiently many ta... | Disliked | zrz@andrew.cmu.edu | Theoretical Models of Learning to Learn : A Machine can only learn if it is biased in some way. Typically the bias is
supplied by hand, for example through the choice of an appropriate set of
features. However, if the learning machine is embedded within an {\em
environment} of related tasks, then it can {\em learn} its... | 0 | zrz@andrew.cmu.edu [SEP] Theoretical Models of Learning to Learn : A Machine can only learn if it is biased in some way. Typically the bias is
supplied by hand, for example through the choice of an appropriate set of
features. However, if the learning machine is embedded within an {\em
environment} of related tasks, th... | 64 |
The Case for Meta-Cognitive Machine Learning: On Model Entropy and Concept Formation in Deep Learning | Machine learning is usually defined in behaviourist terms, where external
validation is the primary mechanism of learning. In this paper, I argue for a
more holistic interpretation in which finding more probable, efficient and
abstract representations is as central to learning as performance. In other
words, machine le... | Disliked | zrz@andrew.cmu.edu | The Case for Meta-Cognitive Machine Learning: On Model Entropy and Concept Formation in Deep Learning : Machine learning is usually defined in behaviourist terms, where external
validation is the primary mechanism of learning. In this paper, I argue for a
more holistic interpretation in which finding more probable, eff... | 0 | zrz@andrew.cmu.edu [SEP] The Case for Meta-Cognitive Machine Learning: On Model Entropy and Concept Formation in Deep Learning : Machine learning is usually defined in behaviourist terms, where external
validation is the primary mechanism of learning. In this paper, I argue for a
more holistic interpretation in which f... | 142 |
High-Precise Robot Arm Manipulation based on Online Iterative Learning and Forward Simulation with Positioning Error Below End-Effector Physical Minimum Displacement | Precision is a crucial performance indicator for robot arms, as high
precision manipulation allows for a wider range of applications. Traditional
methods for improving robot arm precision rely on error compensation. However,
these methods are often not robust and lack adaptability. Learning-based
methods offer greater ... | Liked | jechoi@andrew.cmu.edu | High-Precise Robot Arm Manipulation based on Online Iterative Learning and Forward Simulation with Positioning Error Below End-Effector Physical Minimum Displacement : Precision is a crucial performance indicator for robot arms, as high
precision manipulation allows for a wider range of applications. Traditional
method... | 1 | jechoi@andrew.cmu.edu [SEP] High-Precise Robot Arm Manipulation based on Online Iterative Learning and Forward Simulation with Positioning Error Below End-Effector Physical Minimum Displacement : Precision is a crucial performance indicator for robot arms, as high
precision manipulation allows for a wider range of appl... | 423 |
Mental Models of Adversarial Machine Learning | Although machine learning is widely used in practice, little is known about
practitioners' understanding of potential security challenges. In this work, we
close this substantial gap and contribute a qualitative study focusing on
developers' mental models of the machine learning pipeline and potentially
vulnerable comp... | Disliked | zrz@andrew.cmu.edu | Mental Models of Adversarial Machine Learning : Although machine learning is widely used in practice, little is known about
practitioners' understanding of potential security challenges. In this work, we
close this substantial gap and contribute a qualitative study focusing on
developers' mental models of the machine l... | 0 | zrz@andrew.cmu.edu [SEP] Mental Models of Adversarial Machine Learning : Although machine learning is widely used in practice, little is known about
practitioners' understanding of potential security challenges. In this work, we
close this substantial gap and contribute a qualitative study focusing on
developers' menta... | 111 |
Introduction to deep learning | Deep Learning (DL) has made a major impact on data science in the last
decade. This chapter introduces the basic concepts of this field. It includes
both the basic structures used to design deep neural networks and a brief
survey of some of its popular use cases. | Disliked | zrz@andrew.cmu.edu | Introduction to deep learning : Deep Learning (DL) has made a major impact on data science in the last
decade. This chapter introduces the basic concepts of this field. It includes
both the basic structures used to design deep neural networks and a brief
survey of some of its popular use cases. | 0 | zrz@andrew.cmu.edu [SEP] Introduction to deep learning : Deep Learning (DL) has made a major impact on data science in the last
decade. This chapter introduces the basic concepts of this field. It includes
both the basic structures used to design deep neural networks and a brief
survey of some of its popular use cases. | 201 |
Rethinking Causal Mask Attention for Vision-Language Inference | Causal attention has become a foundational mechanism in autoregressive
vision-language models (VLMs), unifying textual and visual inputs under a
single generative framework. However, existing causal mask-based strategies are
inherited from large language models (LLMs) where they are tailored for
text-only decoding, and... | Liked | zrz@andrew.cmu.edu | Rethinking Causal Mask Attention for Vision-Language Inference : Causal attention has become a foundational mechanism in autoregressive
vision-language models (VLMs), unifying textual and visual inputs under a
single generative framework. However, existing causal mask-based strategies are
inherited from large language ... | 1 | zrz@andrew.cmu.edu [SEP] Rethinking Causal Mask Attention for Vision-Language Inference : Causal attention has become a foundational mechanism in autoregressive
vision-language models (VLMs), unifying textual and visual inputs under a
single generative framework. However, existing causal mask-based strategies are
inher... | 379 |
Asset Pricing and Deep Learning | Traditional machine learning methods have been widely studied in financial
innovation. My study focuses on the application of deep learning methods on
asset pricing. I investigate various deep learning methods for asset pricing,
especially for risk premia measurement. All models take the same set of
predictive signals ... | Liked | zrz@andrew.cmu.edu | Asset Pricing and Deep Learning : Traditional machine learning methods have been widely studied in financial
innovation. My study focuses on the application of deep learning methods on
asset pricing. I investigate various deep learning methods for asset pricing,
especially for risk premia measurement. All models take t... | 1 | zrz@andrew.cmu.edu [SEP] Asset Pricing and Deep Learning : Traditional machine learning methods have been widely studied in financial
innovation. My study focuses on the application of deep learning methods on
asset pricing. I investigate various deep learning methods for asset pricing,
especially for risk premia measu... | 228 |
Human-vehicle Cooperative Visual Perception for Autonomous Driving under Complex Road and Traffic Scenarios | Human-vehicle cooperative driving has become the critical technology of
autonomous driving, which reduces the workload of human drivers. However, the
complex and uncertain road environments bring great challenges to the visual
perception of cooperative systems. And the perception characteristics of
autonomous driving d... | Liked | zrz@andrew.cmu.edu | Human-vehicle Cooperative Visual Perception for Autonomous Driving under Complex Road and Traffic Scenarios : Human-vehicle cooperative driving has become the critical technology of
autonomous driving, which reduces the workload of human drivers. However, the
complex and uncertain road environments bring great challeng... | 1 | zrz@andrew.cmu.edu [SEP] Human-vehicle Cooperative Visual Perception for Autonomous Driving under Complex Road and Traffic Scenarios : Human-vehicle cooperative driving has become the critical technology of
autonomous driving, which reduces the workload of human drivers. However, the
complex and uncertain road environm... | 277 |
Boosting Deep Ensembles with Learning Rate Tuning | The Learning Rate (LR) has a high impact on deep learning training
performance. A common practice is to train a Deep Neural Network (DNN) multiple
times with different LR policies to find the optimal LR policy, which has been
widely recognized as a daunting and costly task. Moreover, multiple times of
DNN training has ... | Disliked | zrz@andrew.cmu.edu | Boosting Deep Ensembles with Learning Rate Tuning : The Learning Rate (LR) has a high impact on deep learning training
performance. A common practice is to train a Deep Neural Network (DNN) multiple
times with different LR policies to find the optimal LR policy, which has been
widely recognized as a daunting and costly... | 0 | zrz@andrew.cmu.edu [SEP] Boosting Deep Ensembles with Learning Rate Tuning : The Learning Rate (LR) has a high impact on deep learning training
performance. A common practice is to train a Deep Neural Network (DNN) multiple
times with different LR policies to find the optimal LR policy, which has been
widely recognized... | 251 |
Deep Learning for Sentiment Analysis : A Survey | Deep learning has emerged as a powerful machine learning technique that
learns multiple layers of representations or features of the data and produces
state-of-the-art prediction results. Along with the success of deep learning in
many other application domains, deep learning is also popularly used in
sentiment analysi... | Liked | zrz@andrew.cmu.edu | Deep Learning for Sentiment Analysis : A Survey : Deep learning has emerged as a powerful machine learning technique that
learns multiple layers of representations or features of the data and produces
state-of-the-art prediction results. Along with the success of deep learning in
many other application domains, deep le... | 1 | zrz@andrew.cmu.edu [SEP] Deep Learning for Sentiment Analysis : A Survey : Deep learning has emerged as a powerful machine learning technique that
learns multiple layers of representations or features of the data and produces
state-of-the-art prediction results. Along with the success of deep learning in
many other app... | 181 |
Deep Neural Networks - A Brief History | Introduction to deep neural networks and their history. | Disliked | zrz@andrew.cmu.edu | Deep Neural Networks - A Brief History : Introduction to deep neural networks and their history. | 0 | zrz@andrew.cmu.edu [SEP] Deep Neural Networks - A Brief History : Introduction to deep neural networks and their history. | 353 |
Vehicle-to-Everything Cooperative Perception for Autonomous Driving | Achieving fully autonomous driving with enhanced safety and efficiency relies
on vehicle-to-everything cooperative perception, which enables vehicles to
share perception data, thereby enhancing situational awareness and overcoming
the limitations of the sensing ability of individual vehicles.
Vehicle-to-everything coop... | Liked | zrz@andrew.cmu.edu | Vehicle-to-Everything Cooperative Perception for Autonomous Driving : Achieving fully autonomous driving with enhanced safety and efficiency relies
on vehicle-to-everything cooperative perception, which enables vehicles to
share perception data, thereby enhancing situational awareness and overcoming
the limitations of ... | 1 | zrz@andrew.cmu.edu [SEP] Vehicle-to-Everything Cooperative Perception for Autonomous Driving : Achieving fully autonomous driving with enhanced safety and efficiency relies
on vehicle-to-everything cooperative perception, which enables vehicles to
share perception data, thereby enhancing situational awareness and overc... | 307 |
Proceedings of the 29th International Conference on Machine Learning (ICML-12) | This is an index to the papers that appear in the Proceedings of the 29th
International Conference on Machine Learning (ICML-12). The conference was held
in Edinburgh, Scotland, June 27th - July 3rd, 2012. | Disliked | zrz@andrew.cmu.edu | Proceedings of the 29th International Conference on Machine Learning (ICML-12) : This is an index to the papers that appear in the Proceedings of the 29th
International Conference on Machine Learning (ICML-12). The conference was held
in Edinburgh, Scotland, June 27th - July 3rd, 2012. | 0 | zrz@andrew.cmu.edu [SEP] Proceedings of the 29th International Conference on Machine Learning (ICML-12) : This is an index to the papers that appear in the Proceedings of the 29th
International Conference on Machine Learning (ICML-12). The conference was held
in Edinburgh, Scotland, June 27th - July 3rd, 2012. | 58 |
A Review of the Convergence of 5G/6G Architecture and Deep Learning | The convergence of 5G architecture and deep learning has gained a lot of
research interests in both the fields of wireless communication and artificial
intelligence. This is because deep learning technologies have been identified
to be the potential driver of the 5G technologies, that make up the 5G
architecture. Hence... | Liked | zrz@andrew.cmu.edu | A Review of the Convergence of 5G/6G Architecture and Deep Learning : The convergence of 5G architecture and deep learning has gained a lot of
research interests in both the fields of wireless communication and artificial
intelligence. This is because deep learning technologies have been identified
to be the potential ... | 1 | zrz@andrew.cmu.edu [SEP] A Review of the Convergence of 5G/6G Architecture and Deep Learning : The convergence of 5G architecture and deep learning has gained a lot of
research interests in both the fields of wireless communication and artificial
intelligence. This is because deep learning technologies have been identi... | 247 |
Bimanual crop manipulation for human-inspired robotic harvesting | Most existing robotic harvesters utilize a unimanual approach; a single arm
grasps the crop and detaches it, either via a detachment movement, or by
cutting its stem with a specially designed gripper/cutter end-effector.
However, such unimanual solutions cannot be applied for sensitive crops and
cluttered environments ... | Liked | jechoi@andrew.cmu.edu | Bimanual crop manipulation for human-inspired robotic harvesting : Most existing robotic harvesters utilize a unimanual approach; a single arm
grasps the crop and detaches it, either via a detachment movement, or by
cutting its stem with a specially designed gripper/cutter end-effector.
However, such unimanual solution... | 1 | jechoi@andrew.cmu.edu [SEP] Bimanual crop manipulation for human-inspired robotic harvesting : Most existing robotic harvesters utilize a unimanual approach; a single arm
grasps the crop and detaches it, either via a detachment movement, or by
cutting its stem with a specially designed gripper/cutter end-effector.
Howe... | 500 |
Quantum-enhanced machine learning | The emerging field of quantum machine learning has the potential to
substantially aid in the problems and scope of artificial intelligence. This is
only enhanced by recent successes in the field of classical machine learning.
In this work we propose an approach for the systematic treatment of machine
learning, from the... | Disliked | zrz@andrew.cmu.edu | Quantum-enhanced machine learning : The emerging field of quantum machine learning has the potential to
substantially aid in the problems and scope of artificial intelligence. This is
only enhanced by recent successes in the field of classical machine learning.
In this work we propose an approach for the systematic tre... | 0 | zrz@andrew.cmu.edu [SEP] Quantum-enhanced machine learning : The emerging field of quantum machine learning has the potential to
substantially aid in the problems and scope of artificial intelligence. This is
only enhanced by recent successes in the field of classical machine learning.
In this work we propose an approa... | 130 |
Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds | Autonomous vehicles may make wrong decisions due to inaccurate detection and
recognition. Therefore, an intelligent vehicle can combine its own data with
that of other vehicles to enhance perceptive ability, and thus improve
detection accuracy and driving safety. However, multi-vehicle cooperative
perception requires t... | Liked | zrz@andrew.cmu.edu | Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds : Autonomous vehicles may make wrong decisions due to inaccurate detection and
recognition. Therefore, an intelligent vehicle can combine its own data with
that of other vehicles to enhance perceptive ability, and thus improve
det... | 1 | zrz@andrew.cmu.edu [SEP] Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds : Autonomous vehicles may make wrong decisions due to inaccurate detection and
recognition. Therefore, an intelligent vehicle can combine its own data with
that of other vehicles to enhance perceptive abil... | 330 |
Engineering problems in machine learning systems | Fatal accidents are a major issue hindering the wide acceptance of
safety-critical systems that employ machine learning and deep learning models,
such as automated driving vehicles. In order to use machine learning in a
safety-critical system, it is necessary to demonstrate the safety and security
of the system through... | Liked | zrz@andrew.cmu.edu | Engineering problems in machine learning systems : Fatal accidents are a major issue hindering the wide acceptance of
safety-critical systems that employ machine learning and deep learning models,
such as automated driving vehicles. In order to use machine learning in a
safety-critical system, it is necessary to demons... | 1 | zrz@andrew.cmu.edu [SEP] Engineering problems in machine learning systems : Fatal accidents are a major issue hindering the wide acceptance of
safety-critical systems that employ machine learning and deep learning models,
such as automated driving vehicles. In order to use machine learning in a
safety-critical system, ... | 138 |
Deep Bayesian Active Learning with Image Data | Even though active learning forms an important pillar of machine learning,
deep learning tools are not prevalent within it. Deep learning poses several
difficulties when used in an active learning setting. First, active learning
(AL) methods generally rely on being able to learn and update models from small
amounts of ... | Disliked | zrz@andrew.cmu.edu | Deep Bayesian Active Learning with Image Data : Even though active learning forms an important pillar of machine learning,
deep learning tools are not prevalent within it. Deep learning poses several
difficulties when used in an active learning setting. First, active learning
(AL) methods generally rely on being able t... | 0 | zrz@andrew.cmu.edu [SEP] Deep Bayesian Active Learning with Image Data : Even though active learning forms an important pillar of machine learning,
deep learning tools are not prevalent within it. Deep learning poses several
difficulties when used in an active learning setting. First, active learning
(AL) methods gener... | 197 |
Interpretations of Deep Learning by Forests and Haar Wavelets | This paper presents a basic property of region dividing of ReLU (rectified
linear unit) deep learning when new layers are successively added, by which two
new perspectives of interpreting deep learning are given. The first is related
to decision trees and forests; we construct a deep learning structure
equivalent to a ... | Liked | zrz@andrew.cmu.edu | Interpretations of Deep Learning by Forests and Haar Wavelets : This paper presents a basic property of region dividing of ReLU (rectified
linear unit) deep learning when new layers are successively added, by which two
new perspectives of interpreting deep learning are given. The first is related
to decision trees and ... | 1 | zrz@andrew.cmu.edu [SEP] Interpretations of Deep Learning by Forests and Haar Wavelets : This paper presents a basic property of region dividing of ReLU (rectified
linear unit) deep learning when new layers are successively added, by which two
new perspectives of interpreting deep learning are given. The first is relat... | 186 |
Deep Causal Learning: Representation, Discovery and Inference | Causal learning has garnered significant attention in recent years because it
reveals the essential relationships that underpin phenomena and delineates the
mechanisms by which the world evolves. Nevertheless, traditional causal
learning methods face numerous challenges and limitations, including
high-dimensional, unst... | Liked | zrz@andrew.cmu.edu | Deep Causal Learning: Representation, Discovery and Inference : Causal learning has garnered significant attention in recent years because it
reveals the essential relationships that underpin phenomena and delineates the
mechanisms by which the world evolves. Nevertheless, traditional causal
learning methods face numer... | 1 | zrz@andrew.cmu.edu [SEP] Deep Causal Learning: Representation, Discovery and Inference : Causal learning has garnered significant attention in recent years because it
reveals the essential relationships that underpin phenomena and delineates the
mechanisms by which the world evolves. Nevertheless, traditional causal
le... | 248 |
Concept-Oriented Deep Learning | Concepts are the foundation of human deep learning, understanding, and
knowledge integration and transfer. We propose concept-oriented deep learning
(CODL) which extends (machine) deep learning with concept representations and
conceptual understanding capability. CODL addresses some of the major
limitations of deep lea... | Disliked | zrz@andrew.cmu.edu | Concept-Oriented Deep Learning : Concepts are the foundation of human deep learning, understanding, and
knowledge integration and transfer. We propose concept-oriented deep learning
(CODL) which extends (machine) deep learning with concept representations and
conceptual understanding capability. CODL addresses some of ... | 0 | zrz@andrew.cmu.edu [SEP] Concept-Oriented Deep Learning : Concepts are the foundation of human deep learning, understanding, and
knowledge integration and transfer. We propose concept-oriented deep learning
(CODL) which extends (machine) deep learning with concept representations and
conceptual understanding capability... | 159 |
An Essay on Optimization Mystery of Deep Learning | Despite the huge empirical success of deep learning, theoretical
understanding of neural networks learning process is still lacking. This is the
reason, why some of its features seem "mysterious". We emphasize two mysteries
of deep learning: generalization mystery, and optimization mystery. In this
essay we review and ... | Liked | zrz@andrew.cmu.edu | An Essay on Optimization Mystery of Deep Learning : Despite the huge empirical success of deep learning, theoretical
understanding of neural networks learning process is still lacking. This is the
reason, why some of its features seem "mysterious". We emphasize two mysteries
of deep learning: generalization mystery, an... | 1 | zrz@andrew.cmu.edu [SEP] An Essay on Optimization Mystery of Deep Learning : Despite the huge empirical success of deep learning, theoretical
understanding of neural networks learning process is still lacking. This is the
reason, why some of its features seem "mysterious". We emphasize two mysteries
of deep learning: g... | 211 |
Julia Language in Machine Learning: Algorithms, Applications, and Open Issues | Machine learning is driving development across many fields in science and
engineering. A simple and efficient programming language could accelerate
applications of machine learning in various fields. Currently, the programming
languages most commonly used to develop machine learning algorithms include
Python, MATLAB, a... | Disliked | zrz@andrew.cmu.edu | Julia Language in Machine Learning: Algorithms, Applications, and Open Issues : Machine learning is driving development across many fields in science and
engineering. A simple and efficient programming language could accelerate
applications of machine learning in various fields. Currently, the programming
languages mos... | 0 | zrz@andrew.cmu.edu [SEP] Julia Language in Machine Learning: Algorithms, Applications, and Open Issues : Machine learning is driving development across many fields in science and
engineering. A simple and efficient programming language could accelerate
applications of machine learning in various fields. Currently, the ... | 113 |
Vision Transformers in Medical Computer Vision -- A Contemplative Retrospection | Recent escalation in the field of computer vision underpins a huddle of
algorithms with the magnificent potential to unravel the information contained
within images. These computer vision algorithms are being practised in medical
image analysis and are transfiguring the perception and interpretation of
Imaging data. Am... | Liked | zrz@andrew.cmu.edu | Vision Transformers in Medical Computer Vision -- A Contemplative Retrospection : Recent escalation in the field of computer vision underpins a huddle of
algorithms with the magnificent potential to unravel the information contained
within images. These computer vision algorithms are being practised in medical
image an... | 1 | zrz@andrew.cmu.edu [SEP] Vision Transformers in Medical Computer Vision -- A Contemplative Retrospection : Recent escalation in the field of computer vision underpins a huddle of
algorithms with the magnificent potential to unravel the information contained
within images. These computer vision algorithms are being prac... | 339 |
Soft Arm-Motor Thrust Characterization for a Pneumatically Actuated Soft Morphing Quadrotor | In this work, an experimental characterization of the configuration space of
a soft, pneumatically actuated morphing quadrotor is presented, with a focus on
precise thrust characterization of its flexible arms, considering the effect of
downwash. Unlike traditional quadrotors, the soft drone has pneumatically
actuated ... | Liked | jechoi@andrew.cmu.edu | Soft Arm-Motor Thrust Characterization for a Pneumatically Actuated Soft Morphing Quadrotor : In this work, an experimental characterization of the configuration space of
a soft, pneumatically actuated morphing quadrotor is presented, with a focus on
precise thrust characterization of its flexible arms, considering the... | 1 | jechoi@andrew.cmu.edu [SEP] Soft Arm-Motor Thrust Characterization for a Pneumatically Actuated Soft Morphing Quadrotor : In this work, an experimental characterization of the configuration space of
a soft, pneumatically actuated morphing quadrotor is presented, with a focus on
precise thrust characterization of its fl... | 460 |
Towards A Rigorous Science of Interpretable Machine Learning | As machine learning systems become ubiquitous, there has been a surge of
interest in interpretable machine learning: systems that provide explanation
for their outputs. These explanations are often used to qualitatively assess
other criteria such as safety or non-discrimination. However, despite the
interest in interpr... | Disliked | zrz@andrew.cmu.edu | Towards A Rigorous Science of Interpretable Machine Learning : As machine learning systems become ubiquitous, there has been a surge of
interest in interpretable machine learning: systems that provide explanation
for their outputs. These explanations are often used to qualitatively assess
other criteria such as safety ... | 0 | zrz@andrew.cmu.edu [SEP] Towards A Rigorous Science of Interpretable Machine Learning : As machine learning systems become ubiquitous, there has been a surge of
interest in interpretable machine learning: systems that provide explanation
for their outputs. These explanations are often used to qualitatively assess
other... | 71 |
Transfer Learning for Voice Activity Detection: A Denoising Deep Neural Network Perspective | Mismatching problem between the source and target noisy corpora severely
hinder the practical use of the machine-learning-based voice activity detection
(VAD). In this paper, we try to address this problem in the transfer learning
prospective. Transfer learning tries to find a common learning machine or a
common featur... | Disliked | zrz@andrew.cmu.edu | Transfer Learning for Voice Activity Detection: A Denoising Deep Neural Network Perspective : Mismatching problem between the source and target noisy corpora severely
hinder the practical use of the machine-learning-based voice activity detection
(VAD). In this paper, we try to address this problem in the transfer lear... | 0 | zrz@andrew.cmu.edu [SEP] Transfer Learning for Voice Activity Detection: A Denoising Deep Neural Network Perspective : Mismatching problem between the source and target noisy corpora severely
hinder the practical use of the machine-learning-based voice activity detection
(VAD). In this paper, we try to address this pro... | 149 |
Scientific Exploration of Challenging Planetary Analog Environments with a Team of Legged Robots | The interest in exploring planetary bodies for scientific investigation and
in-situ resource utilization is ever-rising. Yet, many sites of interest are
inaccessible to state-of-the-art planetary exploration robots because of the
robots' inability to traverse steep slopes, unstructured terrain, and loose
soil. Addition... | Disliked | jechoi@andrew.cmu.edu | Scientific Exploration of Challenging Planetary Analog Environments with a Team of Legged Robots : The interest in exploring planetary bodies for scientific investigation and
in-situ resource utilization is ever-rising. Yet, many sites of interest are
inaccessible to state-of-the-art planetary exploration robots becaus... | 0 | jechoi@andrew.cmu.edu [SEP] Scientific Exploration of Challenging Planetary Analog Environments with a Team of Legged Robots : The interest in exploring planetary bodies for scientific investigation and
in-situ resource utilization is ever-rising. Yet, many sites of interest are
inaccessible to state-of-the-art planeta... | 548 |
PAPRAS: Plug-And-Play Robotic Arm System | This paper presents a novel robotic arm system, named PAPRAS (Plug-And-Play
Robotic Arm System). PAPRAS consists of a portable robotic arm(s), docking
mount(s), and software architecture including a control system. By analyzing
the target task spaces at home, the dimensions and configuration of PAPRAS are
determined. P... | Liked | jechoi@andrew.cmu.edu | PAPRAS: Plug-And-Play Robotic Arm System : This paper presents a novel robotic arm system, named PAPRAS (Plug-And-Play
Robotic Arm System). PAPRAS consists of a portable robotic arm(s), docking
mount(s), and software architecture including a control system. By analyzing
the target task spaces at home, the dimensions an... | 1 | jechoi@andrew.cmu.edu [SEP] PAPRAS: Plug-And-Play Robotic Arm System : This paper presents a novel robotic arm system, named PAPRAS (Plug-And-Play
Robotic Arm System). PAPRAS consists of a portable robotic arm(s), docking
mount(s), and software architecture including a control system. By analyzing
the target task space... | 457 |
The configuration space of a robotic arm in a tunnel | We study the motion of a robotic arm inside a rectangular tunnel. We prove
that the configuration space of all possible positions of the robot is a CAT(0)
cubical complex. This allows us to use techniques from geometric group theory
to find the optimal way of moving the arm from one position to another. We also
compute... | Liked | jechoi@andrew.cmu.edu | The configuration space of a robotic arm in a tunnel : We study the motion of a robotic arm inside a rectangular tunnel. We prove
that the configuration space of all possible positions of the robot is a CAT(0)
cubical complex. This allows us to use techniques from geometric group theory
to find the optimal way of movin... | 1 | jechoi@andrew.cmu.edu [SEP] The configuration space of a robotic arm in a tunnel : We study the motion of a robotic arm inside a rectangular tunnel. We prove
that the configuration space of all possible positions of the robot is a CAT(0)
cubical complex. This allows us to use techniques from geometric group theory
to f... | 472 |
An Anomaly Behavior Analysis Framework for Securing Autonomous Vehicle Perception | As a rapidly growing cyber-physical platform, Autonomous Vehicles (AVs) are
encountering more security challenges as their capabilities continue to expand.
In recent years, adversaries are actively targeting the perception sensors of
autonomous vehicles with sophisticated attacks that are not easily detected by
the veh... | Disliked | zrz@andrew.cmu.edu | An Anomaly Behavior Analysis Framework for Securing Autonomous Vehicle Perception : As a rapidly growing cyber-physical platform, Autonomous Vehicles (AVs) are
encountering more security challenges as their capabilities continue to expand.
In recent years, adversaries are actively targeting the perception sensors of
au... | 0 | zrz@andrew.cmu.edu [SEP] An Anomaly Behavior Analysis Framework for Securing Autonomous Vehicle Perception : As a rapidly growing cyber-physical platform, Autonomous Vehicles (AVs) are
encountering more security challenges as their capabilities continue to expand.
In recent years, adversaries are actively targeting the... | 305 |
Continuous Collision Detection for a Robotic Arm Mounted on a Cable-Driven Parallel Robot | A continuous collision checking method for a cable-driven parallel robot with
an embarked robotic arm is proposed in this paper. The method aims at
validating paths by checking for collisions between any pair of robot bodies
(mobile platform, cables, and arm links). For a pair of bodies, an upper bound
on their relativ... | Liked | jechoi@andrew.cmu.edu | Continuous Collision Detection for a Robotic Arm Mounted on a Cable-Driven Parallel Robot : A continuous collision checking method for a cable-driven parallel robot with
an embarked robotic arm is proposed in this paper. The method aims at
validating paths by checking for collisions between any pair of robot bodies
(mo... | 1 | jechoi@andrew.cmu.edu [SEP] Continuous Collision Detection for a Robotic Arm Mounted on a Cable-Driven Parallel Robot : A continuous collision checking method for a cable-driven parallel robot with
an embarked robotic arm is proposed in this paper. The method aims at
validating paths by checking for collisions between ... | 528 |
Components of Machine Learning: Binding Bits and FLOPS | Many machine learning problems and methods are combinations of three
components: data, hypothesis space and loss function. Different machine
learning methods are obtained as combinations of different choices for the
representation of data, hypothesis space and loss function. After reviewing the
mathematical structure o... | Disliked | zrz@andrew.cmu.edu | Components of Machine Learning: Binding Bits and FLOPS : Many machine learning problems and methods are combinations of three
components: data, hypothesis space and loss function. Different machine
learning methods are obtained as combinations of different choices for the
representation of data, hypothesis space and lo... | 0 | zrz@andrew.cmu.edu [SEP] Components of Machine Learning: Binding Bits and FLOPS : Many machine learning problems and methods are combinations of three
components: data, hypothesis space and loss function. Different machine
learning methods are obtained as combinations of different choices for the
representation of data... | 59 |
Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation | Embodied interaction has been introduced to human-robot interaction (HRI) as
a type of teleoperation, in which users control robot arms with bodily action
via handheld controllers or haptic gloves. Embodied teleoperation has made
robot control intuitive to non-technical users, but differences between humans'
and robots... | Liked | jechoi@andrew.cmu.edu | Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation : Embodied interaction has been introduced to human-robot interaction (HRI) as
a type of teleoperation, in which users control robot arms with bodily action
via handheld controllers or haptic gloves. Embodied teleoperation ha... | 1 | jechoi@andrew.cmu.edu [SEP] Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation : Embodied interaction has been introduced to human-robot interaction (HRI) as
a type of teleoperation, in which users control robot arms with bodily action
via handheld controllers or haptic glove... | 386 |
Stochastic Variational Deep Kernel Learning | Deep kernel learning combines the non-parametric flexibility of kernel
methods with the inductive biases of deep learning architectures. We propose a
novel deep kernel learning model and stochastic variational inference procedure
which generalizes deep kernel learning approaches to enable classification,
multi-task lea... | Disliked | zrz@andrew.cmu.edu | Stochastic Variational Deep Kernel Learning : Deep kernel learning combines the non-parametric flexibility of kernel
methods with the inductive biases of deep learning architectures. We propose a
novel deep kernel learning model and stochastic variational inference procedure
which generalizes deep kernel learning appro... | 0 | zrz@andrew.cmu.edu [SEP] Stochastic Variational Deep Kernel Learning : Deep kernel learning combines the non-parametric flexibility of kernel
methods with the inductive biases of deep learning architectures. We propose a
novel deep kernel learning model and stochastic variational inference procedure
which generalizes d... | 245 |
Towards Modular Machine Learning Solution Development: Benefits and Trade-offs | Machine learning technologies have demonstrated immense capabilities in
various domains. They play a key role in the success of modern businesses.
However, adoption of machine learning technologies has a lot of untouched
potential. Cost of developing custom machine learning solutions that solve
unique business problems... | Liked | zrz@andrew.cmu.edu | Towards Modular Machine Learning Solution Development: Benefits and Trade-offs : Machine learning technologies have demonstrated immense capabilities in
various domains. They play a key role in the success of modern businesses.
However, adoption of machine learning technologies has a lot of untouched
potential. Cost of... | 1 | zrz@andrew.cmu.edu [SEP] Towards Modular Machine Learning Solution Development: Benefits and Trade-offs : Machine learning technologies have demonstrated immense capabilities in
various domains. They play a key role in the success of modern businesses.
However, adoption of machine learning technologies has a lot of unt... | 25 |
Minimax deviation strategies for machine learning and recognition with short learning samples | The article is devoted to the problem of small learning samples in machine
learning. The flaws of maximum likelihood learning and minimax learning are
looked into and the concept of minimax deviation learning is introduced that is
free of those flaws. | Liked | zrz@andrew.cmu.edu | Minimax deviation strategies for machine learning and recognition with short learning samples : The article is devoted to the problem of small learning samples in machine
learning. The flaws of maximum likelihood learning and minimax learning are
looked into and the concept of minimax deviation learning is introduced t... | 1 | zrz@andrew.cmu.edu [SEP] Minimax deviation strategies for machine learning and recognition with short learning samples : The article is devoted to the problem of small learning samples in machine
learning. The flaws of maximum likelihood learning and minimax learning are
looked into and the concept of minimax deviation... | 1 |
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