Publications
Learning Differentiable Programs with Admissible Neural Heuristics
Ameesh Shah, Eric Zhan, Jennifer J. Sun, Abhinav Verma, Yisong Yue, Swarat Chaudhuri
NeurIPS, 2020
Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning
Ishan Durugkar, Elad Liebman, and Peter Stone
IJCAI, 2020
Learning Affordance Landscapes for Interaction Exploration in 3D Environments
T. Nagarajan and. K. Grauman. NeurIPS
NeurIPS, 2020
Neurosymbolic Reinforcement Learning with Formally Verified Exploration
Greg Anderson, Abhinav Verma, Isil Dillig, Swarat Chaudhuri
NeurIPS, 2020
Using Human-Inspired Signals to Disambiguate Navigational Intentions
Justin Hart, Reuth Mirsky, Xuesu Xiao, Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter Stone
ICSR, 2020
Meta-learning for mixed linear regression
Weihao Kong, Raghav Somani, Zhao Song, Sham Kakade, Sewoong Oh
arXiv, 2020
The Gossiping Insert-Eliminate Algorithm for Multi-Agent Bandits
Ronshee Chawla, Abishek Sankararaman, Ayalvadi Ganesh, Sanjay Shakkottai
AISTATS, 2020
Modeling Fashion Influence from Photos
Z. Al-Halah and K. Grauman
IEEE, 2020
Reinforced Grounded Action Transformation for Sim-to-Real Transfer
Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, and Peter Stone
IROS, 2020
Harmonic Decompositions of Convolutional Networks
Meyer Scetbon, Zaid Harchaoui
ICML, 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification
Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt
arXiv, 2020
The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation
Shih-Yun Lo, Shiqi Zhang, and Peter Stone
JAIR, 2020
A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork
Reuth Mirsky, William Macke, Andy Wang, Harel Yedidsion, and Peter Stone
IJCAI, 2020
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning
Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang
ICLR, 2020
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey
Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, and Peter Stone
JMLR, 2020
End-to-End Learning for Retrospective Change-Point Estimation
Corinne Jones, Zaid Harchaoui
MLSP, 2020
Good Systems, Bad Data? Interpretations of AI Hype and Failures
Stephen C. Slota, Kenneth R. Fleischmann, Sherri Greenberg, Nitin Verma, Brenna Cummings, Lan Li, Chris Shenefiel
asis&t, 2020
Generalizing Curricula for Reinforcement Learning
Sanmit Narvekar and Peter Stone
ICML, 2020