activity
20202025
most citedBridgeData V2: A Dataset for Robot Learning at Scale

12 citations · 23 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.LG2024★ 1 cited

Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation

Michelle Pan, Mariah Schrum, Vivek Myers +2

Adaptive brain stimulation can treat neurological conditions such as Parkinson's disease and post-stroke motor deficits by influencing abnormal neural activity. Because of patient…

cs.LG2023

Active Reward Learning from Online Preferences

Vivek Myers, Erdem Bıyık, Dorsa Sadigh

Robot policies need to adapt to human preferences and/or new environments. Human experts may have the domain knowledge required to help robots achieve this adaptation. However, exi…

cs.LG2021

Bayesian Meta-Learning Through Variational Gaussian Processes

Vivek Myers, Nikhil Sardana

Recent advances in the field of meta-learning have tackled domains consisting of large numbers of small ("few-shot") supervised learning tasks. Meta-learning algorithms must be abl…

cs.LG2021★ 2 cited

Learning Multimodal Rewards from Rankings

Vivek Myers, Erdem Bıyık, Nima Anari +1

Learning from human feedback has shown to be a useful approach in acquiring robot reward functions. However, expert feedback is often assumed to be drawn from an underlying unimoda…

cs.LG2020★ 1 cited

A Hierarchical Approach to Scaling Batch Active Search Over Structured Data

Vivek Myers, Peyton Greenside

Active search is the process of identifying high-value data points in a large and often high-dimensional parameter space that can be expensive to evaluate. Traditional active searc…