39 citations · 117 across the 43 of their papers we have counts for
14 papers · 1 filter
Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance
Kelvin Xu, Zheyuan Hu, Ria Doshi +4
Complex and contact-rich robotic manipulation tasks, particularly those that involve multi-fingered hands and underactuated object manipulation, present a significant challenge to…
Learning Robust Real-World Dexterous Grasping Policies via Implicit Shape Augmentation
Zoey Qiuyu Chen, Karl Van Wyk, Yu-Wei Chao +4
Dexterous robotic hands have the capability to interact with a wide variety of household objects to perform tasks like grasping. However, learning robust real world grasping polici…
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity
Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai +2
Reinforcement learning provides an automated framework for learning behaviors from high-level reward specifications, but in practice the choice of reward function can be crucial fo…
Distributionally Adaptive Meta Reinforcement Learning
Anurag Ajay, Abhishek Gupta, Dibya Ghosh +2
Meta-reinforcement learning algorithms provide a data-driven way to acquire policies that quickly adapt to many tasks with varying rewards or dynamics functions. However, learned m…
DexTransfer: Real World Multi-fingered Dexterous Grasping with Minimal Human Demonstrations
Zoey Qiuyu Chen, Karl Van Wyk, Yu-Wei Chao +4
Teaching a multi-fingered dexterous robot to grasp objects in the real world has been a challenging problem due to its high dimensional state and action space. We propose a robot-l…
Superior mechanical properties by exploiting size-effects and multiscale interactions in hierarchically architected foams
Komal Chawla, Abhishek Gupta, Abhijeet S. Bhardwaj +1
Protective applications in extreme environments demand thermally stable materials with superior modulus, strength, and specific energy absorption (SEA) at lightweight. However, the…
Fundamentals of Vehicular Communication Networks with Vehicle Platoons
Kaushlendra Pandey, Kanaka Raju Perumalla, Abhishek K. Gupta +1
Vehicular platooning is a promising way to facilitate efficient movement of vehicles with a shared route. Despite its relevance, the interplay of platooning and the communication p…
Impact of Multiple Fully-Absorbing Receivers in Molecular Communications
Nithin V. Sabu, Abhishek K. Gupta, Neeraj Varshney +1
Molecular communication is a promising solution to enable intra-body communications among nanomachines. However, malicious and non-cooperative receivers can degrade the performance…
Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning
Abhishek Gupta, Corey Lynch, Brandon Kinman +3
Reinforcement learning systems have the potential to enable continuous improvement in unstructured environments, leveraging data collected autonomously. However, in practice these…
Teachable Reinforcement Learning via Advice Distillation
Olivia Watkins, Trevor Darrell, Pieter Abbeel +2
Training automated agents to complete complex tasks in interactive environments is challenging: reinforcement learning requires careful hand-engineering of reward functions, imitat…
Multitask Neuroevolution for Reinforcement Learning with Long and Short Episodes
Nick Zhang, Abhishek Gupta, Zefeng Chen +1
Studies have shown evolution strategies (ES) to be a promising approach for reinforcement learning (RL) with deep neural networks. However, the issue of high sample complexity pers…
The Golden Circle: Creating Socio-technical Alignment in Content Moderation
Abhishek Gupta, Iga Kozlowska, Nga Than
This paper outlines a conceptual framework titled The Golden Circle that describes the roles of actors at individual, organizational, and societal levels, and their dynamics in the…
Combining Varied Learners for Binary Classification using Stacked Generalization
Sruthi Nair, Abhishek Gupta, Raunak Joshi +1
The Machine Learning has various learning algorithms that are better in some or the other aspect when compared with each other but a common error that all algorithms will suffer fr…
State of AI Ethics Report (Volume 6, February 2022)
Abhishek Gupta, Connor Wright, Marianna Bergamaschi Ganapini +2
This report from the Montreal AI Ethics Institute (MAIEI) covers the most salient progress in research and reporting over the second half of 2021 in the field of AI ethics. Particu…