Stanford AI Lab Papers and Talks at ICLR 2022
中文摘要
Stanford AI Lab presents autonomous RL research at ICLR 2022 with papers and videos. Contact authors for more details.
English Summary
Stanford AI Lab is presenting its research, including papers and videos, at the virtual ICLR 2022 conference, held from April 25th to 29th.
The International Conference on Learning Representations (ICLR) 2022 is being hosted virtually from April 25th - April 29th. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about the work that’s happening at Stanford! List of Accepted Papers Autonomous Reinforcement Learning: Formalism and Benchmarking Authors: Archit Sharma*, Kelvin Xu*, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn Contact: architsh@stanford.edu Links: Paper | Website Keywords: reinforcement learning, continual learning, reset-free reinforcement learning MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts Authors: Weixin Liang, James Zou Contact: wxliang@stanford.edu Links: Paper | Video | Website Keywords: benchmark dataset, distribution shift, out-of-domain generalization An Explanation of In-context Learning as Implicit Bayesian Inference Authors: Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma Contact: xie@cs.stanford.edu Links: Paper | Video Keywords: gpt-3, in-context lear…