Title string | Abstract string | Status string | User string | text string | label int64 | combined_text string | __index_level_0__ int64 |
|---|---|---|---|---|---|---|---|
Introducing Visual Perception Token into Multimodal Large Language Model | To utilize visual information, Multimodal Large Language Model (MLLM) relies
on the perception process of its vision encoder. The completeness and accuracy
of visual perception significantly influence the precision of spatial
reasoning, fine-grained understanding, and other tasks. However, MLLM still
lacks the autonomo... | Liked | zrz@andrew.cmu.edu | Introducing Visual Perception Token into Multimodal Large Language Model : To utilize visual information, Multimodal Large Language Model (MLLM) relies
on the perception process of its vision encoder. The completeness and accuracy
of visual perception significantly influence the precision of spatial
reasoning, fine-gra... | 1 | zrz@andrew.cmu.edu [SEP] Introducing Visual Perception Token into Multimodal Large Language Model : To utilize visual information, Multimodal Large Language Model (MLLM) relies
on the perception process of its vision encoder. The completeness and accuracy
of visual perception significantly influence the precision of sp... | 291 |
Control the Soft Robot Arm with its Physical Twin | To exploit the compliant capabilities of soft robot arms we require
controller which can exploit their physical capabilities. Teleoperation,
leveraging a human in the loop, is a key step towards achieving more complex
control strategies. Whilst teleoperation is widely used for rigid robots, for
soft robots we require t... | Liked | jechoi@andrew.cmu.edu | Control the Soft Robot Arm with its Physical Twin : To exploit the compliant capabilities of soft robot arms we require
controller which can exploit their physical capabilities. Teleoperation,
leveraging a human in the loop, is a key step towards achieving more complex
control strategies. Whilst teleoperation is widely... | 1 | jechoi@andrew.cmu.edu [SEP] Control the Soft Robot Arm with its Physical Twin : To exploit the compliant capabilities of soft robot arms we require
controller which can exploit their physical capabilities. Teleoperation,
leveraging a human in the loop, is a key step towards achieving more complex
control strategies. Wh... | 565 |
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... | 395 |
Multi-Arm Robot Task Planning for Fruit Harvesting Using Multi-Agent Reinforcement Learning | The emergence of harvesting robotics offers a promising solution to the issue
of limited agricultural labor resources and the increasing demand for fruits.
Despite notable advancements in the field of harvesting robotics, the
utilization of such technology in orchards is still limited. The key challenge
is to improve o... | Disliked | jechoi@andrew.cmu.edu | Multi-Arm Robot Task Planning for Fruit Harvesting Using Multi-Agent Reinforcement Learning : The emergence of harvesting robotics offers a promising solution to the issue
of limited agricultural labor resources and the increasing demand for fruits.
Despite notable advancements in the field of harvesting robotics, the
... | 0 | jechoi@andrew.cmu.edu [SEP] Multi-Arm Robot Task Planning for Fruit Harvesting Using Multi-Agent Reinforcement Learning : The emergence of harvesting robotics offers a promising solution to the issue
of limited agricultural labor resources and the increasing demand for fruits.
Despite notable advancements in the field ... | 451 |
Deep Divergence Learning | Classical linear metric learning methods have recently been extended along
two distinct lines: deep metric learning methods for learning embeddings of the
data using neural networks, and Bregman divergence learning approaches for
extending learning Euclidean distances to more general divergence measures such
as diverge... | Liked | zrz@andrew.cmu.edu | Deep Divergence Learning : Classical linear metric learning methods have recently been extended along
two distinct lines: deep metric learning methods for learning embeddings of the
data using neural networks, and Bregman divergence learning approaches for
extending learning Euclidean distances to more general divergen... | 1 | zrz@andrew.cmu.edu [SEP] Deep Divergence Learning : Classical linear metric learning methods have recently been extended along
two distinct lines: deep metric learning methods for learning embeddings of the
data using neural networks, and Bregman divergence learning approaches for
extending learning Euclidean distances... | 220 |
Real-time Streaming Perception System for Autonomous Driving | Nowadays, plenty of deep learning technologies are being applied to all
aspects of autonomous driving with promising results. Among them, object
detection is the key to improve the ability of an autonomous agent to perceive
its environment so that it can (re)act. However, previous vision-based object
detectors cannot a... | Liked | zrz@andrew.cmu.edu | Real-time Streaming Perception System for Autonomous Driving : Nowadays, plenty of deep learning technologies are being applied to all
aspects of autonomous driving with promising results. Among them, object
detection is the key to improve the ability of an autonomous agent to perceive
its environment so that it can (r... | 1 | zrz@andrew.cmu.edu [SEP] Real-time Streaming Perception System for Autonomous Driving : Nowadays, plenty of deep learning technologies are being applied to all
aspects of autonomous driving with promising results. Among them, object
detection is the key to improve the ability of an autonomous agent to perceive
its envi... | 302 |
Leveraging Large Language Models for Enhancing Autonomous Vehicle Perception | Autonomous vehicles (AVs) rely on sophisticated perception systems to
interpret their surroundings, a cornerstone for safe navigation and
decision-making. The integration of Large Language Models (LLMs) into AV
perception frameworks offers an innovative approach to address challenges in
dynamic environments, sensor fus... | Liked | zrz@andrew.cmu.edu | Leveraging Large Language Models for Enhancing Autonomous Vehicle Perception : Autonomous vehicles (AVs) rely on sophisticated perception systems to
interpret their surroundings, a cornerstone for safe navigation and
decision-making. The integration of Large Language Models (LLMs) into AV
perception frameworks offers a... | 1 | zrz@andrew.cmu.edu [SEP] Leveraging Large Language Models for Enhancing Autonomous Vehicle Perception : Autonomous vehicles (AVs) rely on sophisticated perception systems to
interpret their surroundings, a cornerstone for safe navigation and
decision-making. The integration of Large Language Models (LLMs) into AV
perce... | 276 |
A Shared Autonomy Reconfigurable Control Framework for Telemanipulation of Multi-arm Systems | Teleoperation is a widely adopted strategy to control robotic manipulators
executing complex tasks that require highly dexterous movements and critical
high-level intelligence. Classical teleoperation schemes are based on either
joystick control, or on more intuitive interfaces which map directly the user
arm motions i... | Liked | jechoi@andrew.cmu.edu | A Shared Autonomy Reconfigurable Control Framework for Telemanipulation of Multi-arm Systems : Teleoperation is a widely adopted strategy to control robotic manipulators
executing complex tasks that require highly dexterous movements and critical
high-level intelligence. Classical teleoperation schemes are based on eit... | 1 | jechoi@andrew.cmu.edu [SEP] A Shared Autonomy Reconfigurable Control Framework for Telemanipulation of Multi-arm Systems : Teleoperation is a widely adopted strategy to control robotic manipulators
executing complex tasks that require highly dexterous movements and critical
high-level intelligence. Classical teleoperat... | 436 |
Deep Online Learning with Stochastic Constraints | Deep learning models are considered to be state-of-the-art in many offline
machine learning tasks. However, many of the techniques developed are not
suitable for online learning tasks. The problem of using deep learning models
with sequential data becomes even harder when several loss functions need to be
considered si... | Disliked | zrz@andrew.cmu.edu | Deep Online Learning with Stochastic Constraints : Deep learning models are considered to be state-of-the-art in many offline
machine learning tasks. However, many of the techniques developed are not
suitable for online learning tasks. The problem of using deep learning models
with sequential data becomes even harder w... | 0 | zrz@andrew.cmu.edu [SEP] Deep Online Learning with Stochastic Constraints : Deep learning models are considered to be state-of-the-art in many offline
machine learning tasks. However, many of the techniques developed are not
suitable for online learning tasks. The problem of using deep learning models
with sequential d... | 254 |
Model Complexity of Deep Learning: A Survey | Model complexity is a fundamental problem in deep learning. In this paper we
conduct a systematic overview of the latest studies on model complexity in deep
learning. Model complexity of deep learning can be categorized into expressive
capacity and effective model complexity. We review the existing studies on
those two... | Disliked | zrz@andrew.cmu.edu | Model Complexity of Deep Learning: A Survey : Model complexity is a fundamental problem in deep learning. In this paper we
conduct a systematic overview of the latest studies on model complexity in deep
learning. Model complexity of deep learning can be categorized into expressive
capacity and effective model complexit... | 0 | zrz@andrew.cmu.edu [SEP] Model Complexity of Deep Learning: A Survey : Model complexity is a fundamental problem in deep learning. In this paper we
conduct a systematic overview of the latest studies on model complexity in deep
learning. Model complexity of deep learning can be categorized into expressive
capacity and ... | 243 |
SpaceOctopus: An Octopus-inspired Motion Planning Framework for Multi-arm Space Robot | Space robots have played a critical role in autonomous maintenance and space
junk removal. Multi-arm space robots can efficiently complete the target
capture and base reorientation tasks due to their flexibility and the
collaborative capabilities between the arms. However, the complex coupling
properties arising from b... | Disliked | jechoi@andrew.cmu.edu | SpaceOctopus: An Octopus-inspired Motion Planning Framework for Multi-arm Space Robot : Space robots have played a critical role in autonomous maintenance and space
junk removal. Multi-arm space robots can efficiently complete the target
capture and base reorientation tasks due to their flexibility and the
collaborativ... | 0 | jechoi@andrew.cmu.edu [SEP] SpaceOctopus: An Octopus-inspired Motion Planning Framework for Multi-arm Space Robot : Space robots have played a critical role in autonomous maintenance and space
junk removal. Multi-arm space robots can efficiently complete the target
capture and base reorientation tasks due to their flex... | 408 |
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... | 12 |
The Tribes of Machine Learning and the Realm of Computer Architecture | Machine learning techniques have influenced the field of computer
architecture like many other fields. This paper studies how the fundamental
machine learning techniques can be applied towards computer architecture
problems. We also provide a detailed survey of computer architecture research
that employs different mach... | Disliked | zrz@andrew.cmu.edu | The Tribes of Machine Learning and the Realm of Computer Architecture : Machine learning techniques have influenced the field of computer
architecture like many other fields. This paper studies how the fundamental
machine learning techniques can be applied towards computer architecture
problems. We also provide a detai... | 0 | zrz@andrew.cmu.edu [SEP] The Tribes of Machine Learning and the Realm of Computer Architecture : Machine learning techniques have influenced the field of computer
architecture like many other fields. This paper studies how the fundamental
machine learning techniques can be applied towards computer architecture
problems... | 33 |
What Really is Deep Learning Doing? | Deep learning has achieved a great success in many areas, from computer
vision to natural language processing, to game playing, and much more. Yet,
what deep learning is really doing is still an open question. There are a lot
of works in this direction. For example, [5] tried to explain deep learning by
group renormali... | Liked | zrz@andrew.cmu.edu | What Really is Deep Learning Doing? : Deep learning has achieved a great success in many areas, from computer
vision to natural language processing, to game playing, and much more. Yet,
what deep learning is really doing is still an open question. There are a lot
of works in this direction. For example, [5] tried to ex... | 1 | zrz@andrew.cmu.edu [SEP] What Really is Deep Learning Doing? : Deep learning has achieved a great success in many areas, from computer
vision to natural language processing, to game playing, and much more. Yet,
what deep learning is really doing is still an open question. There are a lot
of works in this direction. For... | 175 |
Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning | Contrastive vision-language models (e.g. CLIP) are typically created by
updating all the parameters of a vision model and language model through
contrastive training. Can such models be created by a small number of parameter
updates to an already-trained language model and vision model? The literature
describes techniq... | Liked | zrz@andrew.cmu.edu | Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning : Contrastive vision-language models (e.g. CLIP) are typically created by
updating all the parameters of a vision model and language model through
contrastive training. Can such models be created by a small number of parameter
upd... | 1 | zrz@andrew.cmu.edu [SEP] Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning : Contrastive vision-language models (e.g. CLIP) are typically created by
updating all the parameters of a vision model and language model through
contrastive training. Can such models be created by a smal... | 377 |
CLAMGen: Closed-Loop Arm Motion Generation via Multi-view Vision-Based RL | We propose a vision-based reinforcement learning (RL) approach for
closed-loop trajectory generation in an arm reaching problem. Arm trajectory
generation is a fundamental robotics problem which entails finding
collision-free paths to move the robot's body (e.g. arm) in order to satisfy a
goal (e.g. place end-effector ... | Liked | jechoi@andrew.cmu.edu | CLAMGen: Closed-Loop Arm Motion Generation via Multi-view Vision-Based RL : We propose a vision-based reinforcement learning (RL) approach for
closed-loop trajectory generation in an arm reaching problem. Arm trajectory
generation is a fundamental robotics problem which entails finding
collision-free paths to move the ... | 1 | jechoi@andrew.cmu.edu [SEP] CLAMGen: Closed-Loop Arm Motion Generation via Multi-view Vision-Based RL : We propose a vision-based reinforcement learning (RL) approach for
closed-loop trajectory generation in an arm reaching problem. Arm trajectory
generation is a fundamental robotics problem which entails finding
colli... | 568 |
Some Requests for Machine Learning Research from the East African Tech Scene | Based on 46 in-depth interviews with scientists, engineers, and CEOs, this
document presents a list of concrete machine research problems, progress on
which would directly benefit tech ventures in East Africa. | Disliked | zrz@andrew.cmu.edu | Some Requests for Machine Learning Research from the East African Tech Scene : Based on 46 in-depth interviews with scientists, engineers, and CEOs, this
document presents a list of concrete machine research problems, progress on
which would directly benefit tech ventures in East Africa. | 0 | zrz@andrew.cmu.edu [SEP] Some Requests for Machine Learning Research from the East African Tech Scene : Based on 46 in-depth interviews with scientists, engineers, and CEOs, this
document presents a list of concrete machine research problems, progress on
which would directly benefit tech ventures in East Africa. | 99 |
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... | 143 |
Octopus-Swimming-Like Robot with Soft Asymmetric Arms | Underwater vehicles have seen significant development over the past seventy
years. However, bio-inspired propulsion robots are still in their early stages
and require greater interdisciplinary collaboration between biologists and
roboticists. The octopus, one of the most intelligent marine animals, exhibits
remarkable ... | Disliked | jechoi@andrew.cmu.edu | Octopus-Swimming-Like Robot with Soft Asymmetric Arms : Underwater vehicles have seen significant development over the past seventy
years. However, bio-inspired propulsion robots are still in their early stages
and require greater interdisciplinary collaboration between biologists and
roboticists. The octopus, one of t... | 0 | jechoi@andrew.cmu.edu [SEP] Octopus-Swimming-Like Robot with Soft Asymmetric Arms : Underwater vehicles have seen significant development over the past seventy
years. However, bio-inspired propulsion robots are still in their early stages
and require greater interdisciplinary collaboration between biologists and
roboti... | 421 |
Why & When Deep Learning Works: Looking Inside Deep Learnings | The Intel Collaborative Research Institute for Computational Intelligence
(ICRI-CI) has been heavily supporting Machine Learning and Deep Learning
research from its foundation in 2012. We have asked six leading ICRI-CI Deep
Learning researchers to address the challenge of "Why & When Deep Learning
works", with the goal... | Disliked | zrz@andrew.cmu.edu | Why & When Deep Learning Works: Looking Inside Deep Learnings : The Intel Collaborative Research Institute for Computational Intelligence
(ICRI-CI) has been heavily supporting Machine Learning and Deep Learning
research from its foundation in 2012. We have asked six leading ICRI-CI Deep
Learning researchers to address ... | 0 | zrz@andrew.cmu.edu [SEP] Why & When Deep Learning Works: Looking Inside Deep Learnings : The Intel Collaborative Research Institute for Computational Intelligence
(ICRI-CI) has been heavily supporting Machine Learning and Deep Learning
research from its foundation in 2012. We have asked six leading ICRI-CI Deep
Learnin... | 161 |
Language Features Matter: Effective Language Representations for Vision-Language Tasks | Shouldn't language and vision features be treated equally in vision-language
(VL) tasks? Many VL approaches treat the language component as an afterthought,
using simple language models that are either built upon fixed word embeddings
trained on text-only data or are learned from scratch. We believe that language
featu... | Liked | zrz@andrew.cmu.edu | Language Features Matter: Effective Language Representations for Vision-Language Tasks : Shouldn't language and vision features be treated equally in vision-language
(VL) tasks? Many VL approaches treat the language component as an afterthought,
using simple language models that are either built upon fixed word embeddi... | 1 | zrz@andrew.cmu.edu [SEP] Language Features Matter: Effective Language Representations for Vision-Language Tasks : Shouldn't language and vision features be treated equally in vision-language
(VL) tasks? Many VL approaches treat the language component as an afterthought,
using simple language models that are either buil... | 359 |
D3-ARM: High-Dynamic, Dexterous and Fully Decoupled Cable-driven Robotic Arm | Cable transmission enables motors of robotic arm to operate lightweight and
low-inertia joints remotely in various environments, but it also creates issues
with motion coupling and cable routing that can reduce arm's control precision
and performance. In this paper, we present a novel motion decoupling mechanism
with l... | Liked | jechoi@andrew.cmu.edu | D3-ARM: High-Dynamic, Dexterous and Fully Decoupled Cable-driven Robotic Arm : Cable transmission enables motors of robotic arm to operate lightweight and
low-inertia joints remotely in various environments, but it also creates issues
with motion coupling and cable routing that can reduce arm's control precision
and pe... | 1 | jechoi@andrew.cmu.edu [SEP] D3-ARM: High-Dynamic, Dexterous and Fully Decoupled Cable-driven Robotic Arm : Cable transmission enables motors of robotic arm to operate lightweight and
low-inertia joints remotely in various environments, but it also creates issues
with motion coupling and cable routing that can reduce ar... | 432 |
Machine Learning with a Reject Option: A survey | Machine learning models always make a prediction, even when it is likely to
be inaccurate. This behavior should be avoided in many decision support
applications, where mistakes can have severe consequences. Albeit already
studied in 1970, machine learning with rejection recently gained interest. This
machine learning s... | Disliked | zrz@andrew.cmu.edu | Machine Learning with a Reject Option: A survey : Machine learning models always make a prediction, even when it is likely to
be inaccurate. This behavior should be avoided in many decision support
applications, where mistakes can have severe consequences. Albeit already
studied in 1970, machine learning with rejection... | 0 | zrz@andrew.cmu.edu [SEP] Machine Learning with a Reject Option: A survey : Machine learning models always make a prediction, even when it is likely to
be inaccurate. This behavior should be avoided in many decision support
applications, where mistakes can have severe consequences. Albeit already
studied in 1970, machin... | 146 |
Understanding Shared Control for Assistive Robotic Arms | Living a self-determined life independent of human caregivers or fully
autonomous robots is a crucial factor for human dignity and the preservation of
self-worth for people with motor impairments. Assistive robotic solutions -
particularly robotic arms - are frequently deployed in domestic care,
empowering people with ... | Liked | jechoi@andrew.cmu.edu | Understanding Shared Control for Assistive Robotic Arms : Living a self-determined life independent of human caregivers or fully
autonomous robots is a crucial factor for human dignity and the preservation of
self-worth for people with motor impairments. Assistive robotic solutions -
particularly robotic arms - are fre... | 1 | jechoi@andrew.cmu.edu [SEP] Understanding Shared Control for Assistive Robotic Arms : Living a self-determined life independent of human caregivers or fully
autonomous robots is a crucial factor for human dignity and the preservation of
self-worth for people with motor impairments. Assistive robotic solutions -
particu... | 452 |
Energy-Harvesting Distributed Machine Learning | This paper provides a first study of utilizing energy harvesting for
sustainable machine learning in distributed networks. We consider a distributed
learning setup in which a machine learning model is trained over a large number
of devices that can harvest energy from the ambient environment, and develop a
practical le... | Liked | zrz@andrew.cmu.edu | Energy-Harvesting Distributed Machine Learning : This paper provides a first study of utilizing energy harvesting for
sustainable machine learning in distributed networks. We consider a distributed
learning setup in which a machine learning model is trained over a large number
of devices that can harvest energy from th... | 1 | zrz@andrew.cmu.edu [SEP] Energy-Harvesting Distributed Machine Learning : This paper provides a first study of utilizing energy harvesting for
sustainable machine learning in distributed networks. We consider a distributed
learning setup in which a machine learning model is trained over a large number
of devices that c... | 85 |
Acceleration method for generating perception failure scenarios based on editing Markov process | With the rapid advancement of autonomous driving technology, self-driving
cars have become a central focus in the development of future transportation
systems. Scenario generation technology has emerged as a crucial tool for
testing and verifying the safety performance of autonomous driving systems.
Current research in... | Liked | zrz@andrew.cmu.edu | Acceleration method for generating perception failure scenarios based on editing Markov process : With the rapid advancement of autonomous driving technology, self-driving
cars have become a central focus in the development of future transportation
systems. Scenario generation technology has emerged as a crucial tool f... | 1 | zrz@andrew.cmu.edu [SEP] Acceleration method for generating perception failure scenarios based on editing Markov process : With the rapid advancement of autonomous driving technology, self-driving
cars have become a central focus in the development of future transportation
systems. Scenario generation technology has em... | 273 |
Development of a Voice Controlled Robotic Arm | This paper describes a robotic arm with 5 degrees-of-freedom (DOF) which is
controlled by human voice and has been developed in the Mechatronics
Laboratory, CUET. This robotic arm is interfaced with a PC by serial
communication (RS-232). Users' voice command is captured by a microphone, and
this voice is processed by s... | Disliked | jechoi@andrew.cmu.edu | Development of a Voice Controlled Robotic Arm : This paper describes a robotic arm with 5 degrees-of-freedom (DOF) which is
controlled by human voice and has been developed in the Mechatronics
Laboratory, CUET. This robotic arm is interfaced with a PC by serial
communication (RS-232). Users' voice command is captured b... | 0 | jechoi@andrew.cmu.edu [SEP] Development of a Voice Controlled Robotic Arm : This paper describes a robotic arm with 5 degrees-of-freedom (DOF) which is
controlled by human voice and has been developed in the Mechatronics
Laboratory, CUET. This robotic arm is interfaced with a PC by serial
communication (RS-232). Users'... | 426 |
Casting manipulation of unknown string by robot arm | Casting manipulation has been studied to expand the robot's movable range. In
this manipulation, the robot throws and reaches the end effector to a distant
target. Usually, a special casting manipulator, which consists of rigid arm
links and specific flexible linear objects, is constructed for an effective
casting mani... | Liked | jechoi@andrew.cmu.edu | Casting manipulation of unknown string by robot arm : Casting manipulation has been studied to expand the robot's movable range. In
this manipulation, the robot throws and reaches the end effector to a distant
target. Usually, a special casting manipulator, which consists of rigid arm
links and specific flexible linear... | 1 | jechoi@andrew.cmu.edu [SEP] Casting manipulation of unknown string by robot arm : Casting manipulation has been studied to expand the robot's movable range. In
this manipulation, the robot throws and reaches the end effector to a distant
target. Usually, a special casting manipulator, which consists of rigid arm
links ... | 458 |
Quantum Neural Networks: Concepts, Applications, and Challenges | Quantum deep learning is a research field for the use of quantum computing
techniques for training deep neural networks. The research topics and
directions of deep learning and quantum computing have been separated for long
time, however by discovering that quantum circuits can act like artificial
neural networks, quan... | Disliked | zrz@andrew.cmu.edu | Quantum Neural Networks: Concepts, Applications, and Challenges : Quantum deep learning is a research field for the use of quantum computing
techniques for training deep neural networks. The research topics and
directions of deep learning and quantum computing have been separated for long
time, however by discovering t... | 0 | zrz@andrew.cmu.edu [SEP] Quantum Neural Networks: Concepts, Applications, and Challenges : Quantum deep learning is a research field for the use of quantum computing
techniques for training deep neural networks. The research topics and
directions of deep learning and quantum computing have been separated for long
time,... | 166 |
Integrating Learning and Reasoning with Deep Logic Models | Deep learning is very effective at jointly learning feature representations
and classification models, especially when dealing with high dimensional input
patterns. Probabilistic logic reasoning, on the other hand, is capable to take
consistent and robust decisions in complex environments. The integration of
deep learn... | Liked | zrz@andrew.cmu.edu | Integrating Learning and Reasoning with Deep Logic Models : Deep learning is very effective at jointly learning feature representations
and classification models, especially when dealing with high dimensional input
patterns. Probabilistic logic reasoning, on the other hand, is capable to take
consistent and robust deci... | 1 | zrz@andrew.cmu.edu [SEP] Integrating Learning and Reasoning with Deep Logic Models : Deep learning is very effective at jointly learning feature representations
and classification models, especially when dealing with high dimensional input
patterns. Probabilistic logic reasoning, on the other hand, is capable to take
c... | 170 |
Diversity in Machine Learning | Machine learning methods have achieved good performance and been widely
applied in various real-world applications. They can learn the model adaptively
and be better fit for special requirements of different tasks. Generally, a
good machine learning system is composed of plentiful training data, a good
model training p... | Liked | zrz@andrew.cmu.edu | Diversity in Machine Learning : Machine learning methods have achieved good performance and been widely
applied in various real-world applications. They can learn the model adaptively
and be better fit for special requirements of different tasks. Generally, a
good machine learning system is composed of plentiful traini... | 1 | zrz@andrew.cmu.edu [SEP] Diversity in Machine Learning : Machine learning methods have achieved good performance and been widely
applied in various real-world applications. They can learn the model adaptively
and be better fit for special requirements of different tasks. Generally, a
good machine learning system is com... | 134 |
A Neuro-Symbolic Humanlike Arm Controller for Sophia the Robot | We outline the design and construction of novel robotic arms using machine
perception, convolutional neural networks, and symbolic AI for logical control
and affordance indexing. We describe our robotic arms built with a humanlike
mechanical configuration and aesthetic, with 28 degrees of freedom, touch
sensors, and se... | Disliked | jechoi@andrew.cmu.edu | A Neuro-Symbolic Humanlike Arm Controller for Sophia the Robot : We outline the design and construction of novel robotic arms using machine
perception, convolutional neural networks, and symbolic AI for logical control
and affordance indexing. We describe our robotic arms built with a humanlike
mechanical configuration... | 0 | jechoi@andrew.cmu.edu [SEP] A Neuro-Symbolic Humanlike Arm Controller for Sophia the Robot : We outline the design and construction of novel robotic arms using machine
perception, convolutional neural networks, and symbolic AI for logical control
and affordance indexing. We describe our robotic arms built with a humanl... | 439 |
Prismatic Soft Actuator Augments the Workspace of Soft Continuum Robots | Soft robots are promising for manipulation tasks thanks to their compliance,
safety, and high degree of freedom. However, the commonly used bidirectional
continuum segment design means soft robotic manipulators only function in a
limited hemispherical workspace. This work increases a soft robotic arm's
workspace by des... | Liked | jechoi@andrew.cmu.edu | Prismatic Soft Actuator Augments the Workspace of Soft Continuum Robots : Soft robots are promising for manipulation tasks thanks to their compliance,
safety, and high degree of freedom. However, the commonly used bidirectional
continuum segment design means soft robotic manipulators only function in a
limited hemisphe... | 1 | jechoi@andrew.cmu.edu [SEP] Prismatic Soft Actuator Augments the Workspace of Soft Continuum Robots : Soft robots are promising for manipulation tasks thanks to their compliance,
safety, and high degree of freedom. However, the commonly used bidirectional
continuum segment design means soft robotic manipulators only fu... | 480 |
On-the-Fly Learning in a Perpetual Learning Machine | Despite the promise of brain-inspired machine learning, deep neural networks
(DNN) have frustratingly failed to bridge the deceptively large gap between
learning and memory. Here, we introduce a Perpetual Learning Machine; a new
type of DNN that is capable of brain-like dynamic 'on the fly' learning because
it exists i... | Liked | zrz@andrew.cmu.edu | On-the-Fly Learning in a Perpetual Learning Machine : Despite the promise of brain-inspired machine learning, deep neural networks
(DNN) have frustratingly failed to bridge the deceptively large gap between
learning and memory. Here, we introduce a Perpetual Learning Machine; a new
type of DNN that is capable of brain-... | 1 | zrz@andrew.cmu.edu [SEP] On-the-Fly Learning in a Perpetual Learning Machine : Despite the promise of brain-inspired machine learning, deep neural networks
(DNN) have frustratingly failed to bridge the deceptively large gap between
learning and memory. Here, we introduce a Perpetual Learning Machine; a new
type of DNN ... | 67 |
A Survey of Behavior Learning Applications in Robotics -- State of the Art and Perspectives | Recent success of machine learning in many domains has been overwhelming,
which often leads to false expectations regarding the capabilities of behavior
learning in robotics. In this survey, we analyze the current state of machine
learning for robotic behaviors. We will give a broad overview of behaviors that
have been... | Liked | jechoi@andrew.cmu.edu | A Survey of Behavior Learning Applications in Robotics -- State of the Art and Perspectives : Recent success of machine learning in many domains has been overwhelming,
which often leads to false expectations regarding the capabilities of behavior
learning in robotics. In this survey, we analyze the current state of mac... | 1 | jechoi@andrew.cmu.edu [SEP] A Survey of Behavior Learning Applications in Robotics -- State of the Art and Perspectives : Recent success of machine learning in many domains has been overwhelming,
which often leads to false expectations regarding the capabilities of behavior
learning in robotics. In this survey, we anal... | 573 |
Probabilistic Generative Deep Learning for Molecular Design | Probabilistic generative deep learning for molecular design involves the
discovery and design of new molecules and analysis of their structure,
properties and activities by probabilistic generative models using the deep
learning approach. It leverages the existing huge databases and publications of
experimental results... | Disliked | zrz@andrew.cmu.edu | Probabilistic Generative Deep Learning for Molecular Design : Probabilistic generative deep learning for molecular design involves the
discovery and design of new molecules and analysis of their structure,
properties and activities by probabilistic generative models using the deep
learning approach. It leverages the ex... | 0 | zrz@andrew.cmu.edu [SEP] Probabilistic Generative Deep Learning for Molecular Design : Probabilistic generative deep learning for molecular design involves the
discovery and design of new molecules and analysis of their structure,
properties and activities by probabilistic generative models using the deep
learning appr... | 239 |
Bi-Manual Manipulation and Attachment via Sim-to-Real Reinforcement Learning | Most successes in robotic manipulation have been restricted to single-arm
robots, which limits the range of solvable tasks to pick-and-place, insertion,
and objects rearrangement. In contrast, dual and multi arm robot platforms
unlock a rich diversity of problems that can be tackled, such as laundry
folding and executi... | Liked | jechoi@andrew.cmu.edu | Bi-Manual Manipulation and Attachment via Sim-to-Real Reinforcement Learning : Most successes in robotic manipulation have been restricted to single-arm
robots, which limits the range of solvable tasks to pick-and-place, insertion,
and objects rearrangement. In contrast, dual and multi arm robot platforms
unlock a rich... | 1 | jechoi@andrew.cmu.edu [SEP] Bi-Manual Manipulation and Attachment via Sim-to-Real Reinforcement Learning : Most successes in robotic manipulation have been restricted to single-arm
robots, which limits the range of solvable tasks to pick-and-place, insertion,
and objects rearrangement. In contrast, dual and multi arm r... | 544 |
Controlling Assistive Robots with Learned Latent Actions | Assistive robotic arms enable users with physical disabilities to perform
everyday tasks without relying on a caregiver. Unfortunately, the very
dexterity that makes these arms useful also makes them challenging to
teleoperate: the robot has more degrees-of-freedom than the human can directly
coordinate with a handheld... | Liked | jechoi@andrew.cmu.edu | Controlling Assistive Robots with Learned Latent Actions : Assistive robotic arms enable users with physical disabilities to perform
everyday tasks without relying on a caregiver. Unfortunately, the very
dexterity that makes these arms useful also makes them challenging to
teleoperate: the robot has more degrees-of-fre... | 1 | jechoi@andrew.cmu.edu [SEP] Controlling Assistive Robots with Learned Latent Actions : Assistive robotic arms enable users with physical disabilities to perform
everyday tasks without relying on a caregiver. Unfortunately, the very
dexterity that makes these arms useful also makes them challenging to
teleoperate: the r... | 520 |
Model-Assisted Learning for Adaptive Cooperative Perception of Connected Autonomous Vehicles | Cooperative perception (CP) is a key technology to facilitate consistent and
accurate situational awareness for connected and autonomous vehicles (CAVs). To
tackle the network resource inefficiency issue in traditional broadcast-based
CP, unicast-based CP has been proposed to associate CAV pairs for cooperative
percept... | Liked | zrz@andrew.cmu.edu | Model-Assisted Learning for Adaptive Cooperative Perception of Connected Autonomous Vehicles : Cooperative perception (CP) is a key technology to facilitate consistent and
accurate situational awareness for connected and autonomous vehicles (CAVs). To
tackle the network resource inefficiency issue in traditional broadc... | 1 | zrz@andrew.cmu.edu [SEP] Model-Assisted Learning for Adaptive Cooperative Perception of Connected Autonomous Vehicles : Cooperative perception (CP) is a key technology to facilitate consistent and
accurate situational awareness for connected and autonomous vehicles (CAVs). To
tackle the network resource inefficiency is... | 314 |
The many faces of deep learning | Deep learning has sparked a network of mutual interactions between different
disciplines and AI. Naturally, each discipline focuses and interprets the
workings of deep learning in different ways. This diversity of perspectives on
deep learning, from neuroscience to statistical physics, is a rich source of
inspiration t... | Disliked | zrz@andrew.cmu.edu | The many faces of deep learning : Deep learning has sparked a network of mutual interactions between different
disciplines and AI. Naturally, each discipline focuses and interprets the
workings of deep learning in different ways. This diversity of perspectives on
deep learning, from neuroscience to statistical physics,... | 0 | zrz@andrew.cmu.edu [SEP] The many faces of deep learning : Deep learning has sparked a network of mutual interactions between different
disciplines and AI. Naturally, each discipline focuses and interprets the
workings of deep learning in different ways. This diversity of perspectives on
deep learning, from neuroscienc... | 227 |
Fast Heuristic Scheduling and Trajectory Planning for Robotic Fruit Harvesters with Multiple Cartesian Arms | This work proposes a fast heuristic algorithm for the coupled scheduling and
trajectory planning of multiple Cartesian robotic arms harvesting fruits. Our
method partitions the workspace, assigns fruit-picking sequences to arms,
determines tight and feasible fruit-picking schedules and vehicle travel speed,
and generat... | Liked | jechoi@andrew.cmu.edu | Fast Heuristic Scheduling and Trajectory Planning for Robotic Fruit Harvesters with Multiple Cartesian Arms : This work proposes a fast heuristic algorithm for the coupled scheduling and
trajectory planning of multiple Cartesian robotic arms harvesting fruits. Our
method partitions the workspace, assigns fruit-picking ... | 1 | jechoi@andrew.cmu.edu [SEP] Fast Heuristic Scheduling and Trajectory Planning for Robotic Fruit Harvesters with Multiple Cartesian Arms : This work proposes a fast heuristic algorithm for the coupled scheduling and
trajectory planning of multiple Cartesian robotic arms harvesting fruits. Our
method partitions the works... | 444 |
Quantum memristors for neuromorphic quantum machine learning | Quantum machine learning may permit to realize more efficient machine
learning calculations with near-term quantum devices. Among the diverse quantum
machine learning paradigms which are currently being considered, quantum
memristors are promising as a way of combining, in the same quantum hardware, a
unitary evolution... | Disliked | zrz@andrew.cmu.edu | Quantum memristors for neuromorphic quantum machine learning : Quantum machine learning may permit to realize more efficient machine
learning calculations with near-term quantum devices. Among the diverse quantum
machine learning paradigms which are currently being considered, quantum
memristors are promising as a way ... | 0 | zrz@andrew.cmu.edu [SEP] Quantum memristors for neuromorphic quantum machine learning : Quantum machine learning may permit to realize more efficient machine
learning calculations with near-term quantum devices. Among the diverse quantum
machine learning paradigms which are currently being considered, quantum
memristor... | 63 |
Teaching Uncertainty Quantification in Machine Learning through Use Cases | Uncertainty in machine learning is not generally taught as general knowledge
in Machine Learning course curricula. In this paper we propose a short
curriculum for a course about uncertainty in machine learning, and complement
the course with a selection of use cases, aimed to trigger discussion and let
students play wi... | Disliked | zrz@andrew.cmu.edu | Teaching Uncertainty Quantification in Machine Learning through Use Cases : Uncertainty in machine learning is not generally taught as general knowledge
in Machine Learning course curricula. In this paper we propose a short
curriculum for a course about uncertainty in machine learning, and complement
the course with a ... | 0 | zrz@andrew.cmu.edu [SEP] Teaching Uncertainty Quantification in Machine Learning through Use Cases : Uncertainty in machine learning is not generally taught as general knowledge
in Machine Learning course curricula. In this paper we propose a short
curriculum for a course about uncertainty in machine learning, and comp... | 80 |
Monitoring of Perception Systems: Deterministic, Probabilistic, and Learning-based Fault Detection and Identification | This paper investigates runtime monitoring of perception systems. Perception
is a critical component of high-integrity applications of robotics and
autonomous systems, such as self-driving cars. In these applications, failure
of perception systems may put human life at risk, and a broad adoption of these
technologies r... | Liked | zrz@andrew.cmu.edu | Monitoring of Perception Systems: Deterministic, Probabilistic, and Learning-based Fault Detection and Identification : This paper investigates runtime monitoring of perception systems. Perception
is a critical component of high-integrity applications of robotics and
autonomous systems, such as self-driving cars. In th... | 1 | zrz@andrew.cmu.edu [SEP] Monitoring of Perception Systems: Deterministic, Probabilistic, and Learning-based Fault Detection and Identification : This paper investigates runtime monitoring of perception systems. Perception
is a critical component of high-integrity applications of robotics and
autonomous systems, such as... | 308 |
Visions in Theoretical Computer Science: A Report on the TCS Visioning Workshop 2020 | Theoretical computer science (TCS) is a subdiscipline of computer science
that studies the mathematical foundations of computational and algorithmic
processes and interactions. Work in this field is often recognized by its
emphasis on mathematical technique and rigor. At the heart of the field are
questions surrounding... | Disliked | zrz@andrew.cmu.edu | Visions in Theoretical Computer Science: A Report on the TCS Visioning Workshop 2020 : Theoretical computer science (TCS) is a subdiscipline of computer science
that studies the mathematical foundations of computational and algorithmic
processes and interactions. Work in this field is often recognized by its
emphasis o... | 0 | zrz@andrew.cmu.edu [SEP] Visions in Theoretical Computer Science: A Report on the TCS Visioning Workshop 2020 : Theoretical computer science (TCS) is a subdiscipline of computer science
that studies the mathematical foundations of computational and algorithmic
processes and interactions. Work in this field is often rec... | 362 |
Towards a Crowd Analytic Framework For Crowd Management in Majid-al-Haram | The scared cities of Makkah Al Mukarramah and Madina Al Munawarah host
millions of pilgrims every year. During Hajj, the movement of large number of
people has a unique spatial and temporal constraints, which makes Hajj one of
toughest challenges for crowd management. In this paper, we propose a computer
vision based f... | Disliked | zrz@andrew.cmu.edu | Towards a Crowd Analytic Framework For Crowd Management in Majid-al-Haram : The scared cities of Makkah Al Mukarramah and Madina Al Munawarah host
millions of pilgrims every year. During Hajj, the movement of large number of
people has a unique spatial and temporal constraints, which makes Hajj one of
toughest challeng... | 0 | zrz@andrew.cmu.edu [SEP] Towards a Crowd Analytic Framework For Crowd Management in Majid-al-Haram : The scared cities of Makkah Al Mukarramah and Madina Al Munawarah host
millions of pilgrims every year. During Hajj, the movement of large number of
people has a unique spatial and temporal constraints, which makes Hajj... | 364 |
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. | Liked | 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. | 1 | 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. | 198 |
Deep Causal Learning for Robotic Intelligence | This invited review discusses causal learning in the context of robotic
intelligence. The paper introduced the psychological findings on causal
learning in human cognition, then it introduced the traditional statistical
solutions on causal discovery and causal inference. The paper reviewed recent
deep causal learning a... | Disliked | zrz@andrew.cmu.edu | Deep Causal Learning for Robotic Intelligence : This invited review discusses causal learning in the context of robotic
intelligence. The paper introduced the psychological findings on causal
learning in human cognition, then it introduced the traditional statistical
solutions on causal discovery and causal inference. ... | 0 | zrz@andrew.cmu.edu [SEP] Deep Causal Learning for Robotic Intelligence : This invited review discusses causal learning in the context of robotic
intelligence. The paper introduced the psychological findings on causal
learning in human cognition, then it introduced the traditional statistical
solutions on causal discove... | 185 |
Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review | Grid-centric perception is a crucial field for mobile robot perception and
navigation. Nonetheless, grid-centric perception is less prevalent than
object-centric perception as autonomous vehicles need to accurately perceive
highly dynamic, large-scale traffic scenarios and the complexity and
computational costs of grid... | Liked | zrz@andrew.cmu.edu | Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review : Grid-centric perception is a crucial field for mobile robot perception and
navigation. Nonetheless, grid-centric perception is less prevalent than
object-centric perception as autonomous vehicles need to accurately perceive
highly... | 1 | zrz@andrew.cmu.edu [SEP] Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review : Grid-centric perception is a crucial field for mobile robot perception and
navigation. Nonetheless, grid-centric perception is less prevalent than
object-centric perception as autonomous vehicles need to a... | 306 |
Unknown Delay for Adversarial Bandit Setting with Multiple Play | This paper addresses the problem of unknown delays in adversarial multi-armed
bandit (MAB) with multiple play. Existing work on similar game setting focused
on only the case where the learner selects an arm in each round. However, there
are lots of applications in robotics where a learner needs to select more than
one ... | Liked | jechoi@andrew.cmu.edu | Unknown Delay for Adversarial Bandit Setting with Multiple Play : This paper addresses the problem of unknown delays in adversarial multi-armed
bandit (MAB) with multiple play. Existing work on similar game setting focused
on only the case where the learner selects an arm in each round. However, there
are lots of appli... | 1 | jechoi@andrew.cmu.edu [SEP] Unknown Delay for Adversarial Bandit Setting with Multiple Play : This paper addresses the problem of unknown delays in adversarial multi-armed
bandit (MAB) with multiple play. Existing work on similar game setting focused
on only the case where the learner selects an arm in each round. Howe... | 557 |
Design and Implementation of a DTMF Based Pick and Place Robotic Arm | In recent times, developments in field of communication and robotics has
progressed with leaps and bounds. In addition, the blend of both disciplines
has contributed heavily in making human life easier and better. So in this work
while making use of both the aforementioned technologies, a procedure for
design and imple... | Liked | jechoi@andrew.cmu.edu | Design and Implementation of a DTMF Based Pick and Place Robotic Arm : In recent times, developments in field of communication and robotics has
progressed with leaps and bounds. In addition, the blend of both disciplines
has contributed heavily in making human life easier and better. So in this work
while making use of... | 1 | jechoi@andrew.cmu.edu [SEP] Design and Implementation of a DTMF Based Pick and Place Robotic Arm : In recent times, developments in field of communication and robotics has
progressed with leaps and bounds. In addition, the blend of both disciplines
has contributed heavily in making human life easier and better. So in t... | 547 |
TF.Learn: TensorFlow's High-level Module for Distributed Machine Learning | TF.Learn is a high-level Python module for distributed machine learning
inside TensorFlow. It provides an easy-to-use Scikit-learn style interface to
simplify the process of creating, configuring, training, evaluating, and
experimenting a machine learning model. TF.Learn integrates a wide range of
state-of-art machine ... | Liked | zrz@andrew.cmu.edu | TF.Learn: TensorFlow's High-level Module for Distributed Machine Learning : TF.Learn is a high-level Python module for distributed machine learning
inside TensorFlow. It provides an easy-to-use Scikit-learn style interface to
simplify the process of creating, configuring, training, evaluating, and
experimenting a machi... | 1 | zrz@andrew.cmu.edu [SEP] TF.Learn: TensorFlow's High-level Module for Distributed Machine Learning : TF.Learn is a high-level Python module for distributed machine learning
inside TensorFlow. It provides an easy-to-use Scikit-learn style interface to
simplify the process of creating, configuring, training, evaluating, ... | 98 |
Computer Stereo Vision for Autonomous Driving | As an important component of autonomous systems, autonomous car perception
has had a big leap with recent advances in parallel computing architectures.
With the use of tiny but full-feature embedded supercomputers, computer stereo
vision has been prevalently applied in autonomous cars for depth perception.
The two key ... | Liked | zrz@andrew.cmu.edu | Computer Stereo Vision for Autonomous Driving : As an important component of autonomous systems, autonomous car perception
has had a big leap with recent advances in parallel computing architectures.
With the use of tiny but full-feature embedded supercomputers, computer stereo
vision has been prevalently applied in au... | 1 | zrz@andrew.cmu.edu [SEP] Computer Stereo Vision for Autonomous Driving : As an important component of autonomous systems, autonomous car perception
has had a big leap with recent advances in parallel computing architectures.
With the use of tiny but full-feature embedded supercomputers, computer stereo
vision has been ... | 313 |
Bayesian Optimization for Machine Learning : A Practical Guidebook | The engineering of machine learning systems is still a nascent field; relying
on a seemingly daunting collection of quickly evolving tools and best
practices. It is our hope that this guidebook will serve as a useful resource
for machine learning practitioners looking to take advantage of Bayesian
optimization techniqu... | Liked | zrz@andrew.cmu.edu | Bayesian Optimization for Machine Learning : A Practical Guidebook : The engineering of machine learning systems is still a nascent field; relying
on a seemingly daunting collection of quickly evolving tools and best
practices. It is our hope that this guidebook will serve as a useful resource
for machine learning prac... | 1 | zrz@andrew.cmu.edu [SEP] Bayesian Optimization for Machine Learning : A Practical Guidebook : The engineering of machine learning systems is still a nascent field; relying
on a seemingly daunting collection of quickly evolving tools and best
practices. It is our hope that this guidebook will serve as a useful resource
... | 69 |
MLBench: How Good Are Machine Learning Clouds for Binary Classification Tasks on Structured Data? | We conduct an empirical study of machine learning functionalities provided by
major cloud service providers, which we call machine learning clouds. Machine
learning clouds hold the promise of hiding all the sophistication of running
large-scale machine learning: Instead of specifying how to run a machine
learning task,... | Liked | zrz@andrew.cmu.edu | MLBench: How Good Are Machine Learning Clouds for Binary Classification Tasks on Structured Data? : We conduct an empirical study of machine learning functionalities provided by
major cloud service providers, which we call machine learning clouds. Machine
learning clouds hold the promise of hiding all the sophisticatio... | 1 | zrz@andrew.cmu.edu [SEP] MLBench: How Good Are Machine Learning Clouds for Binary Classification Tasks on Structured Data? : We conduct an empirical study of machine learning functionalities provided by
major cloud service providers, which we call machine learning clouds. Machine
learning clouds hold the promise of hid... | 32 |
Human Arm Pose Estimation with a Shoulder-worn Force-Myography Device for Human-Robot Interaction | Accurate human pose estimation is essential for effective Human-Robot
Interaction (HRI). By observing a user's arm movements, robots can respond
appropriately, whether it's providing assistance or avoiding collisions. While
visual perception offers potential for human pose estimation, it can be
hindered by factors like... | Liked | jechoi@andrew.cmu.edu | Human Arm Pose Estimation with a Shoulder-worn Force-Myography Device for Human-Robot Interaction : Accurate human pose estimation is essential for effective Human-Robot
Interaction (HRI). By observing a user's arm movements, robots can respond
appropriately, whether it's providing assistance or avoiding collisions. Wh... | 1 | jechoi@andrew.cmu.edu [SEP] Human Arm Pose Estimation with a Shoulder-worn Force-Myography Device for Human-Robot Interaction : Accurate human pose estimation is essential for effective Human-Robot
Interaction (HRI). By observing a user's arm movements, robots can respond
appropriately, whether it's providing assistanc... | 437 |
Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics | We introduce Matched Machine Learning, a framework that combines the
flexibility of machine learning black boxes with the interpretability of
matching, a longstanding tool in observational causal inference.
Interpretability is paramount in many high-stakes application of causal
inference. Current tools for nonparametri... | Disliked | zrz@andrew.cmu.edu | Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics : We introduce Matched Machine Learning, a framework that combines the
flexibility of machine learning black boxes with the interpretability of
matching, a longstanding tool in observational causal inference.
Interpret... | 0 | zrz@andrew.cmu.edu [SEP] Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics : We introduce Matched Machine Learning, a framework that combines the
flexibility of machine learning black boxes with the interpretability of
matching, a longstanding tool in observational ca... | 129 |
WiCV 2021: The Eighth Women In Computer Vision Workshop | In this paper, we present the details of Women in Computer Vision Workshop -
WiCV 2021, organized alongside the virtual CVPR 2021. It provides a voice to a
minority (female) group in the computer vision community and focuses on
increasing the visibility of these researchers, both in academia and industry.
WiCV believes... | Disliked | zrz@andrew.cmu.edu | WiCV 2021: The Eighth Women In Computer Vision Workshop : In this paper, we present the details of Women in Computer Vision Workshop -
WiCV 2021, organized alongside the virtual CVPR 2021. It provides a voice to a
minority (female) group in the computer vision community and focuses on
increasing the visibility of these... | 0 | zrz@andrew.cmu.edu [SEP] WiCV 2021: The Eighth Women In Computer Vision Workshop : In this paper, we present the details of Women in Computer Vision Workshop -
WiCV 2021, organized alongside the virtual CVPR 2021. It provides a voice to a
minority (female) group in the computer vision community and focuses on
increasin... | 371 |
Learning to Centralize Dual-Arm Assembly | Robotic manipulators are widely used in modern manufacturing processes.
However, their deployment in unstructured environments remains an open problem.
To deal with the variety, complexity, and uncertainty of real-world
manipulation tasks, it is essential to develop a flexible framework with
reduced assumptions on the ... | Liked | jechoi@andrew.cmu.edu | Learning to Centralize Dual-Arm Assembly : Robotic manipulators are widely used in modern manufacturing processes.
However, their deployment in unstructured environments remains an open problem.
To deal with the variety, complexity, and uncertainty of real-world
manipulation tasks, it is essential to develop a flexible... | 1 | jechoi@andrew.cmu.edu [SEP] Learning to Centralize Dual-Arm Assembly : Robotic manipulators are widely used in modern manufacturing processes.
However, their deployment in unstructured environments remains an open problem.
To deal with the variety, complexity, and uncertainty of real-world
manipulation tasks, it is ess... | 477 |
A Survey of Optimization Methods from a Machine Learning Perspective | Machine learning develops rapidly, which has made many theoretical
breakthroughs and is widely applied in various fields. Optimization, as an
important part of machine learning, has attracted much attention of
researchers. With the exponential growth of data amount and the increase of
model complexity, optimization met... | Liked | zrz@andrew.cmu.edu | A Survey of Optimization Methods from a Machine Learning Perspective : Machine learning develops rapidly, which has made many theoretical
breakthroughs and is widely applied in various fields. Optimization, as an
important part of machine learning, has attracted much attention of
researchers. With the exponential growt... | 1 | zrz@andrew.cmu.edu [SEP] A Survey of Optimization Methods from a Machine Learning Perspective : Machine learning develops rapidly, which has made many theoretical
breakthroughs and is widely applied in various fields. Optimization, as an
important part of machine learning, has attracted much attention of
researchers. W... | 42 |
DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving | In the field of autonomous driving, two important features of autonomous
driving car systems are the explainability of decision logic and the accuracy
of environmental perception. This paper introduces DME-Driver, a new autonomous
driving system that enhances the performance and reliability of autonomous
driving system... | Liked | zrz@andrew.cmu.edu | DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving : In the field of autonomous driving, two important features of autonomous
driving car systems are the explainability of decision logic and the accuracy
of environmental perception. This paper introduces DME-Driver, a new autonom... | 1 | zrz@andrew.cmu.edu [SEP] DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving : In the field of autonomous driving, two important features of autonomous
driving car systems are the explainability of decision logic and the accuracy
of environmental perception. This paper introduces ... | 295 |
Financial Time Series Data Processing for Machine Learning | This article studies the financial time series data processing for machine
learning. It introduces the most frequent scaling methods, then compares the
resulting stationarity and preservation of useful information for trend
forecasting. It proposes an empirical test based on the capability to learn
simple data relation... | Liked | zrz@andrew.cmu.edu | Financial Time Series Data Processing for Machine Learning : This article studies the financial time series data processing for machine
learning. It introduces the most frequent scaling methods, then compares the
resulting stationarity and preservation of useful information for trend
forecasting. It proposes an empiric... | 1 | zrz@andrew.cmu.edu [SEP] Financial Time Series Data Processing for Machine Learning : This article studies the financial time series data processing for machine
learning. It introduces the most frequent scaling methods, then compares the
resulting stationarity and preservation of useful information for trend
forecastin... | 120 |
Combining Deep Learning with Good Old-Fashioned Machine Learning | We present a comprehensive, stacking-based framework for combining deep
learning with good old-fashioned machine learning, called Deep GOld. Our
framework involves ensemble selection from 51 retrained pretrained deep
networks as first-level models, and 10 machine-learning algorithms as
second-level models. Enabled by t... | Liked | zrz@andrew.cmu.edu | Combining Deep Learning with Good Old-Fashioned Machine Learning : We present a comprehensive, stacking-based framework for combining deep
learning with good old-fashioned machine learning, called Deep GOld. Our
framework involves ensemble selection from 51 retrained pretrained deep
networks as first-level models, and ... | 1 | zrz@andrew.cmu.edu [SEP] Combining Deep Learning with Good Old-Fashioned Machine Learning : We present a comprehensive, stacking-based framework for combining deep
learning with good old-fashioned machine learning, called Deep GOld. Our
framework involves ensemble selection from 51 retrained pretrained deep
networks as... | 193 |
Machine Learning for Clinical Predictive Analytics | In this chapter, we provide a brief overview of applying machine learning
techniques for clinical prediction tasks. We begin with a quick introduction to
the concepts of machine learning and outline some of the most common machine
learning algorithms. Next, we demonstrate how to apply the algorithms with
appropriate to... | Disliked | zrz@andrew.cmu.edu | Machine Learning for Clinical Predictive Analytics : In this chapter, we provide a brief overview of applying machine learning
techniques for clinical prediction tasks. We begin with a quick introduction to
the concepts of machine learning and outline some of the most common machine
learning algorithms. Next, we demons... | 0 | zrz@andrew.cmu.edu [SEP] Machine Learning for Clinical Predictive Analytics : In this chapter, we provide a brief overview of applying machine learning
techniques for clinical prediction tasks. We begin with a quick introduction to
the concepts of machine learning and outline some of the most common machine
learning al... | 4 |
Augmented Body Communicator: Enhancing daily body expression for people with upper limb limitations through LLM and a robotic arm | Individuals with upper limb movement limitations face challenges in
interacting with others. Although robotic arms are currently used primarily for
functional tasks, there is considerable potential to explore ways to enhance
users' body language capabilities during social interactions. This paper
introduces an Augmente... | Liked | jechoi@andrew.cmu.edu | Augmented Body Communicator: Enhancing daily body expression for people with upper limb limitations through LLM and a robotic arm : Individuals with upper limb movement limitations face challenges in
interacting with others. Although robotic arms are currently used primarily for
functional tasks, there is considerable ... | 1 | jechoi@andrew.cmu.edu [SEP] Augmented Body Communicator: Enhancing daily body expression for people with upper limb limitations through LLM and a robotic arm : Individuals with upper limb movement limitations face challenges in
interacting with others. Although robotic arms are currently used primarily for
functional t... | 466 |
Mathematical Perspective of Machine Learning | We take a closer look at some theoretical challenges of Machine Learning as a
function approximation, gradient descent as the default optimization algorithm,
limitations of fixed length and width networks and a different approach to RNNs
from a mathematical perspective. | Disliked | zrz@andrew.cmu.edu | Mathematical Perspective of Machine Learning : We take a closer look at some theoretical challenges of Machine Learning as a
function approximation, gradient descent as the default optimization algorithm,
limitations of fixed length and width networks and a different approach to RNNs
from a mathematical perspective. | 0 | zrz@andrew.cmu.edu [SEP] Mathematical Perspective of Machine Learning : We take a closer look at some theoretical challenges of Machine Learning as a
function approximation, gradient descent as the default optimization algorithm,
limitations of fixed length and width networks and a different approach to RNNs
from a mat... | 45 |
Malleable Agents for Re-Configurable Robotic Manipulators | Re-configurable robots have more utility and flexibility for many real-world
tasks. Designing a learning agent to operate such robots requires adapting to
different configurations. Here, we focus on robotic arms with multiple rigid
links connected by joints. We propose a deep reinforcement learning agent with
sequence ... | Liked | jechoi@andrew.cmu.edu | Malleable Agents for Re-Configurable Robotic Manipulators : Re-configurable robots have more utility and flexibility for many real-world
tasks. Designing a learning agent to operate such robots requires adapting to
different configurations. Here, we focus on robotic arms with multiple rigid
links connected by joints. W... | 1 | jechoi@andrew.cmu.edu [SEP] Malleable Agents for Re-Configurable Robotic Manipulators : Re-configurable robots have more utility and flexibility for many real-world
tasks. Designing a learning agent to operate such robots requires adapting to
different configurations. Here, we focus on robotic arms with multiple rigid
... | 428 |
Harnessing with Twisting: Single-Arm Deformable Linear Object Manipulation for Industrial Harnessing Task | Wire-harnessing tasks pose great challenges to be automated by the robot due
to the complex dynamics and unpredictable behavior of the deformable wire.
Traditional methods, often reliant on dual-robot arms or tactile sensing, face
limitations in adaptability, cost, and scalability. This paper introduces a
novel single-... | Liked | jechoi@andrew.cmu.edu | Harnessing with Twisting: Single-Arm Deformable Linear Object Manipulation for Industrial Harnessing Task : Wire-harnessing tasks pose great challenges to be automated by the robot due
to the complex dynamics and unpredictable behavior of the deformable wire.
Traditional methods, often reliant on dual-robot arms or tac... | 1 | jechoi@andrew.cmu.edu [SEP] Harnessing with Twisting: Single-Arm Deformable Linear Object Manipulation for Industrial Harnessing Task : Wire-harnessing tasks pose great challenges to be automated by the robot due
to the complex dynamics and unpredictable behavior of the deformable wire.
Traditional methods, often relia... | 491 |
Metal Wire Manipulation Planning for 3D Curving -- How a Low Payload Robot Can Use a Bending Machine to Bend Stiff Metal Wire | This paper presents a combined task and motion planner for a robot arm to
carry out 3D metal wire curving tasks by collaborating with a bending machine.
We assume a collaborative robot that is safe to work in a human environment but
has a weak payload to bend objects with large stiffness, and developed a
combined plann... | Liked | jechoi@andrew.cmu.edu | Metal Wire Manipulation Planning for 3D Curving -- How a Low Payload Robot Can Use a Bending Machine to Bend Stiff Metal Wire : This paper presents a combined task and motion planner for a robot arm to
carry out 3D metal wire curving tasks by collaborating with a bending machine.
We assume a collaborative robot that is... | 1 | jechoi@andrew.cmu.edu [SEP] Metal Wire Manipulation Planning for 3D Curving -- How a Low Payload Robot Can Use a Bending Machine to Bend Stiff Metal Wire : This paper presents a combined task and motion planner for a robot arm to
carry out 3D metal wire curving tasks by collaborating with a bending machine.
We assume a... | 530 |
Ethics and Creativity in Computer Vision | This paper offers a retrospective of what we learnt from organizing the
workshop *Ethical Considerations in Creative applications of Computer Vision*
at CVPR 2021 conference and, prior to that, a series of workshops on *Computer
Vision for Fashion, Art and Design* at ECCV 2018, ICCV 2019, and CVPR 2020. We
hope this re... | Disliked | zrz@andrew.cmu.edu | Ethics and Creativity in Computer Vision : This paper offers a retrospective of what we learnt from organizing the
workshop *Ethical Considerations in Creative applications of Computer Vision*
at CVPR 2021 conference and, prior to that, a series of workshops on *Computer
Vision for Fashion, Art and Design* at ECCV 2018... | 0 | zrz@andrew.cmu.edu [SEP] Ethics and Creativity in Computer Vision : This paper offers a retrospective of what we learnt from organizing the
workshop *Ethical Considerations in Creative applications of Computer Vision*
at CVPR 2021 conference and, prior to that, a series of workshops on *Computer
Vision for Fashion, Art... | 361 |
Transferability in Deep Learning: A Survey | The success of deep learning algorithms generally depends on large-scale
data, while humans appear to have inherent ability of knowledge transfer, by
recognizing and applying relevant knowledge from previous learning experiences
when encountering and solving unseen tasks. Such an ability to acquire and
reuse knowledge ... | Disliked | zrz@andrew.cmu.edu | Transferability in Deep Learning: A Survey : The success of deep learning algorithms generally depends on large-scale
data, while humans appear to have inherent ability of knowledge transfer, by
recognizing and applying relevant knowledge from previous learning experiences
when encountering and solving unseen tasks. Su... | 0 | zrz@andrew.cmu.edu [SEP] Transferability in Deep Learning: A Survey : The success of deep learning algorithms generally depends on large-scale
data, while humans appear to have inherent ability of knowledge transfer, by
recognizing and applying relevant knowledge from previous learning experiences
when encountering and... | 177 |
Learning Dexterous Manipulation with Quantized Hand State | Dexterous robotic hands enable robots to perform complex manipulations that
require fine-grained control and adaptability. Achieving such manipulation is
challenging because the high degrees of freedom tightly couple hand and arm
motions, making learning and control difficult. Successful dexterous
manipulation relies n... | Liked | jechoi@andrew.cmu.edu | Learning Dexterous Manipulation with Quantized Hand State : Dexterous robotic hands enable robots to perform complex manipulations that
require fine-grained control and adaptability. Achieving such manipulation is
challenging because the high degrees of freedom tightly couple hand and arm
motions, making learning and c... | 1 | jechoi@andrew.cmu.edu [SEP] Learning Dexterous Manipulation with Quantized Hand State : Dexterous robotic hands enable robots to perform complex manipulations that
require fine-grained control and adaptability. Achieving such manipulation is
challenging because the high degrees of freedom tightly couple hand and arm
mo... | 471 |
Extracting Built Environment Features for Planning Research with Computer Vision: A Review and Discussion of State-of-the-Art Approaches | This is an extended abstract for a presentation at The 17th International
Conference on CUPUM - Computational Urban Planning and Urban Management in June
2021. This study presents an interdisciplinary synthesis of the
state-of-the-art approaches in computer vision technologies to extract built
environment features that... | Disliked | zrz@andrew.cmu.edu | Extracting Built Environment Features for Planning Research with Computer Vision: A Review and Discussion of State-of-the-Art Approaches : This is an extended abstract for a presentation at The 17th International
Conference on CUPUM - Computational Urban Planning and Urban Management in June
2021. This study presents a... | 0 | zrz@andrew.cmu.edu [SEP] Extracting Built Environment Features for Planning Research with Computer Vision: A Review and Discussion of State-of-the-Art Approaches : This is an extended abstract for a presentation at The 17th International
Conference on CUPUM - Computational Urban Planning and Urban Management in June
20... | 352 |
Lale: Consistent Automated Machine Learning | Automated machine learning makes it easier for data scientists to develop
pipelines by searching over possible choices for hyperparameters, algorithms,
and even pipeline topologies. Unfortunately, the syntax for automated machine
learning tools is inconsistent with manual machine learning, with each other,
and with err... | Liked | zrz@andrew.cmu.edu | Lale: Consistent Automated Machine Learning : Automated machine learning makes it easier for data scientists to develop
pipelines by searching over possible choices for hyperparameters, algorithms,
and even pipeline topologies. Unfortunately, the syntax for automated machine
learning tools is inconsistent with manual m... | 1 | zrz@andrew.cmu.edu [SEP] Lale: Consistent Automated Machine Learning : Automated machine learning makes it easier for data scientists to develop
pipelines by searching over possible choices for hyperparameters, algorithms,
and even pipeline topologies. Unfortunately, the syntax for automated machine
learning tools is i... | 74 |
Faster Deep Q-learning using Neural Episodic Control | The research on deep reinforcement learning which estimates Q-value by deep
learning has been attracted the interest of researchers recently. In deep
reinforcement learning, it is important to efficiently learn the experiences
that an agent has collected by exploring environment. We propose NEC2DQN that
improves learni... | Disliked | zrz@andrew.cmu.edu | Faster Deep Q-learning using Neural Episodic Control : The research on deep reinforcement learning which estimates Q-value by deep
learning has been attracted the interest of researchers recently. In deep
reinforcement learning, it is important to efficiently learn the experiences
that an agent has collected by explori... | 0 | zrz@andrew.cmu.edu [SEP] Faster Deep Q-learning using Neural Episodic Control : The research on deep reinforcement learning which estimates Q-value by deep
learning has been attracted the interest of researchers recently. In deep
reinforcement learning, it is important to efficiently learn the experiences
that an agent... | 253 |
Machine Learning as Ecology | Machine learning methods have had spectacular success on numerous problems.
Here we show that a prominent class of learning algorithms - including Support
Vector Machines (SVMs) -- have a natural interpretation in terms of ecological
dynamics. We use these ideas to design new online SVM algorithms that exploit
ecologic... | Disliked | zrz@andrew.cmu.edu | Machine Learning as Ecology : Machine learning methods have had spectacular success on numerous problems.
Here we show that a prominent class of learning algorithms - including Support
Vector Machines (SVMs) -- have a natural interpretation in terms of ecological
dynamics. We use these ideas to design new online SVM al... | 0 | zrz@andrew.cmu.edu [SEP] Machine Learning as Ecology : Machine learning methods have had spectacular success on numerous problems.
Here we show that a prominent class of learning algorithms - including Support
Vector Machines (SVMs) -- have a natural interpretation in terms of ecological
dynamics. We use these ideas to... | 106 |
Data Pricing in Machine Learning Pipelines | Machine learning is disruptive. At the same time, machine learning can only
succeed by collaboration among many parties in multiple steps naturally as
pipelines in an eco-system, such as collecting data for possible machine
learning applications, collaboratively training models by multiple parties and
delivering machin... | Liked | zrz@andrew.cmu.edu | Data Pricing in Machine Learning Pipelines : Machine learning is disruptive. At the same time, machine learning can only
succeed by collaboration among many parties in multiple steps naturally as
pipelines in an eco-system, such as collecting data for possible machine
learning applications, collaboratively training mod... | 1 | zrz@andrew.cmu.edu [SEP] Data Pricing in Machine Learning Pipelines : Machine learning is disruptive. At the same time, machine learning can only
succeed by collaboration among many parties in multiple steps naturally as
pipelines in an eco-system, such as collecting data for possible machine
learning applications, col... | 36 |
Vision-Based Shape Reconstruction of Soft Continuum Arms Using a Geometric Strain Parametrization | Interest in soft continuum arms has increased as their inherent material
elasticity enables safe and adaptive interactions with the environment. However
to achieve full autonomy in these arms, accurate three-dimensional shape
sensing is needed. Vision-based solutions have been found to be effective in
estimating the sh... | Liked | jechoi@andrew.cmu.edu | Vision-Based Shape Reconstruction of Soft Continuum Arms Using a Geometric Strain Parametrization : Interest in soft continuum arms has increased as their inherent material
elasticity enables safe and adaptive interactions with the environment. However
to achieve full autonomy in these arms, accurate three-dimensional ... | 1 | jechoi@andrew.cmu.edu [SEP] Vision-Based Shape Reconstruction of Soft Continuum Arms Using a Geometric Strain Parametrization : Interest in soft continuum arms has increased as their inherent material
elasticity enables safe and adaptive interactions with the environment. However
to achieve full autonomy in these arms,... | 558 |
Information Theory and its Relation to Machine Learning | In this position paper, I first describe a new perspective on machine
learning (ML) by four basic problems (or levels), namely, "What to learn?",
"How to learn?", "What to evaluate?", and "What to adjust?". The paper stresses
more on the first level of "What to learn?", or "Learning Target Selection".
Towards this prim... | Disliked | zrz@andrew.cmu.edu | Information Theory and its Relation to Machine Learning : In this position paper, I first describe a new perspective on machine
learning (ML) by four basic problems (or levels), namely, "What to learn?",
"How to learn?", "What to evaluate?", and "What to adjust?". The paper stresses
more on the first level of "What to ... | 0 | zrz@andrew.cmu.edu [SEP] Information Theory and its Relation to Machine Learning : In this position paper, I first describe a new perspective on machine
learning (ML) by four basic problems (or levels), namely, "What to learn?",
"How to learn?", "What to evaluate?", and "What to adjust?". The paper stresses
more on the... | 124 |
A New Robot Arm Calibration Method Based on Cubic Interpolated Beetle Antennae Search Approach | Industrial robot arms are extensively important for intelligent
manufacturing. An industrial robot arm commonly enjoys its high repetitive
positioning accuracy while suffering from its low absolute positioning
accuracy, which greatly restricts its application in high-precision
manufacture, like automobile manufacture. ... | Liked | jechoi@andrew.cmu.edu | A New Robot Arm Calibration Method Based on Cubic Interpolated Beetle Antennae Search Approach : Industrial robot arms are extensively important for intelligent
manufacturing. An industrial robot arm commonly enjoys its high repetitive
positioning accuracy while suffering from its low absolute positioning
accuracy, whi... | 1 | jechoi@andrew.cmu.edu [SEP] A New Robot Arm Calibration Method Based on Cubic Interpolated Beetle Antennae Search Approach : Industrial robot arms are extensively important for intelligent
manufacturing. An industrial robot arm commonly enjoys its high repetitive
positioning accuracy while suffering from its low absolu... | 463 |
Ten-year Survival Prediction for Breast Cancer Patients | This report assesses different machine learning approaches to 10-year
survival prediction of breast cancer patients. | Disliked | zrz@andrew.cmu.edu | Ten-year Survival Prediction for Breast Cancer Patients : This report assesses different machine learning approaches to 10-year
survival prediction of breast cancer patients. | 0 | zrz@andrew.cmu.edu [SEP] Ten-year Survival Prediction for Breast Cancer Patients : This report assesses different machine learning approaches to 10-year
survival prediction of breast cancer patients. | 47 |
Discussion on Mechanical Learning and Learning Machine | Mechanical learning is a computing system that is based on a set of simple
and fixed rules, and can learn from incoming data. A learning machine is a
system that realizes mechanical learning. Importantly, we emphasis that it is
based on a set of simple and fixed rules, contrasting to often called machine
learning that ... | Disliked | zrz@andrew.cmu.edu | Discussion on Mechanical Learning and Learning Machine : Mechanical learning is a computing system that is based on a set of simple
and fixed rules, and can learn from incoming data. A learning machine is a
system that realizes mechanical learning. Importantly, we emphasis that it is
based on a set of simple and fixed ... | 0 | zrz@andrew.cmu.edu [SEP] Discussion on Mechanical Learning and Learning Machine : Mechanical learning is a computing system that is based on a set of simple
and fixed rules, and can learn from incoming data. A learning machine is a
system that realizes mechanical learning. Importantly, we emphasis that it is
based on a... | 125 |
Research Experience of an Undergraduate Student in Computer Vision and Robotics | This paper focuses on the educational journey of a computer engineering
undergraduate student venturing into the domain of computer vision and
robotics. It explores how optical flow and its applications can be used to
detect moving objects when a camera undergoes translational motion,
highlighting the challenges encoun... | Disliked | zrz@andrew.cmu.edu | Research Experience of an Undergraduate Student in Computer Vision and Robotics : This paper focuses on the educational journey of a computer engineering
undergraduate student venturing into the domain of computer vision and
robotics. It explores how optical flow and its applications can be used to
detect moving object... | 0 | zrz@andrew.cmu.edu [SEP] Research Experience of an Undergraduate Student in Computer Vision and Robotics : This paper focuses on the educational journey of a computer engineering
undergraduate student venturing into the domain of computer vision and
robotics. It explores how optical flow and its applications can be use... | 381 |
Prioritized Hierarchical Compliance Control for Dual-Arm Robot Stable Clamping | When a dual-arm robot clamps a rigid object in an environment for human
beings, the environment or the collaborating human will impose incidental
disturbance on the operated object or the robot arm, leading to clamping
failure, damaging the robot even hurting the human. This research proposes a
prioritized hierarchical... | Liked | jechoi@andrew.cmu.edu | Prioritized Hierarchical Compliance Control for Dual-Arm Robot Stable Clamping : When a dual-arm robot clamps a rigid object in an environment for human
beings, the environment or the collaborating human will impose incidental
disturbance on the operated object or the robot arm, leading to clamping
failure, damaging th... | 1 | jechoi@andrew.cmu.edu [SEP] Prioritized Hierarchical Compliance Control for Dual-Arm Robot Stable Clamping : When a dual-arm robot clamps a rigid object in an environment for human
beings, the environment or the collaborating human will impose incidental
disturbance on the operated object or the robot arm, leading to c... | 405 |
Examining the legibility of humanoid robot arm movements in a pointing task | Human--robot interaction requires robots whose actions are legible, allowing
humans to interpret, predict, and feel safe around them. This study
investigates the legibility of humanoid robot arm movements in a pointing task,
aiming to understand how humans predict robot intentions from truncated
movements and bodily cu... | Liked | jechoi@andrew.cmu.edu | Examining the legibility of humanoid robot arm movements in a pointing task : Human--robot interaction requires robots whose actions are legible, allowing
humans to interpret, predict, and feel safe around them. This study
investigates the legibility of humanoid robot arm movements in a pointing task,
aiming to underst... | 1 | jechoi@andrew.cmu.edu [SEP] Examining the legibility of humanoid robot arm movements in a pointing task : Human--robot interaction requires robots whose actions are legible, allowing
humans to interpret, predict, and feel safe around them. This study
investigates the legibility of humanoid robot arm movements in a poin... | 468 |
A Secure and Efficient Multi-Object Grasping Detection Approach for Robotic Arms | Robotic arms are widely used in automatic industries. However, with wide
applications of deep learning in robotic arms, there are new challenges such as
the allocation of grasping computing power and the growing demand for security.
In this work, we propose a robotic arm grasping approach based on deep learning
and edg... | Liked | jechoi@andrew.cmu.edu | A Secure and Efficient Multi-Object Grasping Detection Approach for Robotic Arms : Robotic arms are widely used in automatic industries. However, with wide
applications of deep learning in robotic arms, there are new challenges such as
the allocation of grasping computing power and the growing demand for security.
In t... | 1 | jechoi@andrew.cmu.edu [SEP] A Secure and Efficient Multi-Object Grasping Detection Approach for Robotic Arms : Robotic arms are widely used in automatic industries. However, with wide
applications of deep learning in robotic arms, there are new challenges such as
the allocation of grasping computing power and the growi... | 465 |
The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism | Computer vision and other biometrics data science applications have commenced
a new project of profiling people. Rather than using 'transaction generated
information', these systems measure the 'real world' and produce an assessment
of the 'world state' - in this case an assessment of some individual trait.
Instead of ... | Disliked | zrz@andrew.cmu.edu | The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism : Computer vision and other biometrics data science applications have commenced
a new project of profiling people. Rather than using 'transaction generated
information', these systems measure the 'real world' and produce an assessm... | 0 | zrz@andrew.cmu.edu [SEP] The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism : Computer vision and other biometrics data science applications have commenced
a new project of profiling people. Rather than using 'transaction generated
information', these systems measure the 'real worl... | 384 |
Efficient Medical Vision-Language Alignment Through Adapting Masked Vision Models | Medical vision-language alignment through cross-modal contrastive learning
shows promising performance in image-text matching tasks, such as retrieval and
zero-shot classification. However, conventional cross-modal contrastive
learning (CLIP-based) methods suffer from suboptimal visual representation
capabilities, whic... | Liked | zrz@andrew.cmu.edu | Efficient Medical Vision-Language Alignment Through Adapting Masked Vision Models : Medical vision-language alignment through cross-modal contrastive learning
shows promising performance in image-text matching tasks, such as retrieval and
zero-shot classification. However, conventional cross-modal contrastive
learning ... | 1 | zrz@andrew.cmu.edu [SEP] Efficient Medical Vision-Language Alignment Through Adapting Masked Vision Models : Medical vision-language alignment through cross-modal contrastive learning
shows promising performance in image-text matching tasks, such as retrieval and
zero-shot classification. However, conventional cross-mo... | 357 |
Accelerating Deep Learning with Shrinkage and Recall | Deep Learning is a very powerful machine learning model. Deep Learning trains
a large number of parameters for multiple layers and is very slow when data is
in large scale and the architecture size is large. Inspired from the shrinking
technique used in accelerating computation of Support Vector Machines (SVM)
algorith... | Disliked | zrz@andrew.cmu.edu | Accelerating Deep Learning with Shrinkage and Recall : Deep Learning is a very powerful machine learning model. Deep Learning trains
a large number of parameters for multiple layers and is very slow when data is
in large scale and the architecture size is large. Inspired from the shrinking
technique used in acceleratin... | 0 | zrz@andrew.cmu.edu [SEP] Accelerating Deep Learning with Shrinkage and Recall : Deep Learning is a very powerful machine learning model. Deep Learning trains
a large number of parameters for multiple layers and is very slow when data is
in large scale and the architecture size is large. Inspired from the shrinking
tech... | 207 |
An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning | We propose a clustering-based iterative algorithm to solve certain
optimization problems in machine learning, where we start the algorithm by
aggregating the original data, solving the problem on aggregated data, and then
in subsequent steps gradually disaggregate the aggregated data. We apply the
algorithm to common m... | Disliked | zrz@andrew.cmu.edu | An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning : We propose a clustering-based iterative algorithm to solve certain
optimization problems in machine learning, where we start the algorithm by
aggregating the original data, solving the problem on aggregated data, and then
in ... | 0 | zrz@andrew.cmu.edu [SEP] An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning : We propose a clustering-based iterative algorithm to solve certain
optimization problems in machine learning, where we start the algorithm by
aggregating the original data, solving the problem on aggr... | 65 |
Automated Machine Learning on Graphs: A Survey | Machine learning on graphs has been extensively studied in both academic and
industry. However, as the literature on graph learning booms with a vast number
of emerging methods and techniques, it becomes increasingly difficult to
manually design the optimal machine learning algorithm for different
graph-related tasks. ... | Liked | zrz@andrew.cmu.edu | Automated Machine Learning on Graphs: A Survey : Machine learning on graphs has been extensively studied in both academic and
industry. However, as the literature on graph learning booms with a vast number
of emerging methods and techniques, it becomes increasingly difficult to
manually design the optimal machine learn... | 1 | zrz@andrew.cmu.edu [SEP] Automated Machine Learning on Graphs: A Survey : Machine learning on graphs has been extensively studied in both academic and
industry. However, as the literature on graph learning booms with a vast number
of emerging methods and techniques, it becomes increasingly difficult to
manually design ... | 91 |
IKDiffuser: A Generative Inverse Kinematics Solver for Multi-arm Robots via Diffusion Model | Solving Inverse Kinematics (IK) problems is fundamental to robotics, but has
primarily been successful with single serial manipulators. For multi-arm
robotic systems, IK remains challenging due to complex self-collisions, coupled
joints, and high-dimensional redundancy. These complexities make traditional IK
solvers sl... | Liked | jechoi@andrew.cmu.edu | IKDiffuser: A Generative Inverse Kinematics Solver for Multi-arm Robots via Diffusion Model : Solving Inverse Kinematics (IK) problems is fundamental to robotics, but has
primarily been successful with single serial manipulators. For multi-arm
robotic systems, IK remains challenging due to complex self-collisions, coup... | 1 | jechoi@andrew.cmu.edu [SEP] IKDiffuser: A Generative Inverse Kinematics Solver for Multi-arm Robots via Diffusion Model : Solving Inverse Kinematics (IK) problems is fundamental to robotics, but has
primarily been successful with single serial manipulators. For multi-arm
robotic systems, IK remains challenging due to c... | 406 |
Learning over time using a neuromorphic adaptive control algorithm for robotic arms | In this paper, we explore the ability of a robot arm to learn the underlying
operation space defined by the positions (x, y, z) that the arm's end-effector
can reach, including disturbances, by deploying and thoroughly evaluating a
Spiking Neural Network SNN-based adaptive control algorithm. While traditional
control a... | Liked | jechoi@andrew.cmu.edu | Learning over time using a neuromorphic adaptive control algorithm for robotic arms : In this paper, we explore the ability of a robot arm to learn the underlying
operation space defined by the positions (x, y, z) that the arm's end-effector
can reach, including disturbances, by deploying and thoroughly evaluating a
Sp... | 1 | jechoi@andrew.cmu.edu [SEP] Learning over time using a neuromorphic adaptive control algorithm for robotic arms : In this paper, we explore the ability of a robot arm to learn the underlying
operation space defined by the positions (x, y, z) that the arm's end-effector
can reach, including disturbances, by deploying an... | 414 |
Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition | A deep learning approach has been widely applied in sequence modeling
problems. In terms of automatic speech recognition (ASR), its performance has
significantly been improved by increasing large speech corpus and deeper neural
network. Especially, recurrent neural network and deep convolutional neural
network have bee... | Disliked | zrz@andrew.cmu.edu | Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition : A deep learning approach has been widely applied in sequence modeling
problems. In terms of automatic speech recognition (ASR), its performance has
significantly been improved by increasing large speech corpus and deeper neural
... | 0 | zrz@andrew.cmu.edu [SEP] Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition : A deep learning approach has been widely applied in sequence modeling
problems. In terms of automatic speech recognition (ASR), its performance has
significantly been improved by increasing large speech ... | 221 |
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... | 263 |
Differential Transformer-driven 6G Physical Layer for Collaborative Perception Enhancement | The emergence of 6G wireless networks promises to revolutionize vehicular
communications by enabling ultra-reliable, low-latency, and high-capacity data
exchange. In this context, collaborative perception techniques, where multiple
vehicles or infrastructure nodes cooperate to jointly receive and decode
transmitted sig... | Disliked | zrz@andrew.cmu.edu | Differential Transformer-driven 6G Physical Layer for Collaborative Perception Enhancement : The emergence of 6G wireless networks promises to revolutionize vehicular
communications by enabling ultra-reliable, low-latency, and high-capacity data
exchange. In this context, collaborative perception techniques, where mult... | 0 | zrz@andrew.cmu.edu [SEP] Differential Transformer-driven 6G Physical Layer for Collaborative Perception Enhancement : The emergence of 6G wireless networks promises to revolutionize vehicular
communications by enabling ultra-reliable, low-latency, and high-capacity data
exchange. In this context, collaborative percepti... | 328 |
A Survey on Deep Learning for Skeleton-Based Human Animation | Human character animation is often critical in entertainment content
production, including video games, virtual reality or fiction films. To this
end, deep neural networks drive most recent advances through deep learning and
deep reinforcement learning. In this article, we propose a comprehensive survey
on the state-of... | Liked | zrz@andrew.cmu.edu | A Survey on Deep Learning for Skeleton-Based Human Animation : Human character animation is often critical in entertainment content
production, including video games, virtual reality or fiction films. To this
end, deep neural networks drive most recent advances through deep learning and
deep reinforcement learning. In ... | 1 | zrz@andrew.cmu.edu [SEP] A Survey on Deep Learning for Skeleton-Based Human Animation : Human character animation is often critical in entertainment content
production, including video games, virtual reality or fiction films. To this
end, deep neural networks drive most recent advances through deep learning and
deep re... | 229 |
A Dual-arm Robot that Autonomously Lifts Up and Tumbles Heavy Plates Using Crane Pulley Blocks | This paper develops a planner that plans the action sequences and motion for
a dual-arm robot to lift up and flip heavy plates using crane pulley blocks.
The problem is motivated by the low payload of modern collaborative robots.
Instead of directly manipulating heavy plates that collaborative robots cannot
afford, the... | Disliked | jechoi@andrew.cmu.edu | A Dual-arm Robot that Autonomously Lifts Up and Tumbles Heavy Plates Using Crane Pulley Blocks : This paper develops a planner that plans the action sequences and motion for
a dual-arm robot to lift up and flip heavy plates using crane pulley blocks.
The problem is motivated by the low payload of modern collaborative r... | 0 | jechoi@andrew.cmu.edu [SEP] A Dual-arm Robot that Autonomously Lifts Up and Tumbles Heavy Plates Using Crane Pulley Blocks : This paper develops a planner that plans the action sequences and motion for
a dual-arm robot to lift up and flip heavy plates using crane pulley blocks.
The problem is motivated by the low paylo... | 391 |
A Survey Analyzing Generalization in Deep Reinforcement Learning | Reinforcement learning research obtained significant success and attention
with the utilization of deep neural networks to solve problems in high
dimensional state or action spaces. While deep reinforcement learning policies
are currently being deployed in many different fields from medical applications
to large langua... | Liked | zrz@andrew.cmu.edu | A Survey Analyzing Generalization in Deep Reinforcement Learning : Reinforcement learning research obtained significant success and attention
with the utilization of deep neural networks to solve problems in high
dimensional state or action spaces. While deep reinforcement learning policies
are currently being deployed... | 1 | zrz@andrew.cmu.edu [SEP] A Survey Analyzing Generalization in Deep Reinforcement Learning : Reinforcement learning research obtained significant success and attention
with the utilization of deep neural networks to solve problems in high
dimensional state or action spaces. While deep reinforcement learning policies
are... | 174 |
Manipulability optimization for multi-arm teleoperation | Teleoperation provides a way for human operators to guide robots in
situations where full autonomy is challenging or where direct human
intervention is required. It can also be an important tool to teach robots in
order to achieve autonomous behaviour later on. The increased availability of
collaborative robot arms and... | Liked | jechoi@andrew.cmu.edu | Manipulability optimization for multi-arm teleoperation : Teleoperation provides a way for human operators to guide robots in
situations where full autonomy is challenging or where direct human
intervention is required. It can also be an important tool to teach robots in
order to achieve autonomous behaviour later on. ... | 1 | jechoi@andrew.cmu.edu [SEP] Manipulability optimization for multi-arm teleoperation : Teleoperation provides a way for human operators to guide robots in
situations where full autonomy is challenging or where direct human
intervention is required. It can also be an important tool to teach robots in
order to achieve aut... | 14 |
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