Publications
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Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning
Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang
ICLR, 2020
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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
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End-to-End Learning for Retrospective Change-Point Estimation
Corinne Jones, Zaid Harchaoui
MLSP, 2020
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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
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Generalizing Curricula for Reinforcement Learning
Sanmit Narvekar and Peter Stone
ICML, 2020
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First-order Optimization for Superquantile-based Supervised Learning
Yassine Laguel, Jérome Malick, Zaid Harchaoui
MLSP, 2020
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Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon
Zihan Zhang, Xiangyang Ji, Simon S. Du
arXiv, 2020
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Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
Daniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum
ICML, 2020
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Learning Deep ReLU Networks is Fixed Parameter Tractable
Sitan Chen, Adam R. Klivans, Raghu Meka
arXiv, 2020
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Learning to Improve Multi-Robot Hallway Navigation
Jin-Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone
CoRL, 2020
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Entanglement is Necessary for Optimal Quantum Property Testing
Sebastien Bubeck, Sitan Chen, Jerry Li
arXiv, 2020
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Adaptive Sampling to Reduce Disparate Performance
Jacob Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Jie (Claire) Zhang
arXiv, 2020
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Value Alignment Verification
Daniel S. Brown, Jordan Schneioder, Scott Niekum
NeurIPS, 2020
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Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent.
Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam Klivans
ICML, 2020
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Kernel and Rich Regimes in Overparametrized Models
Blake Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro
PMLR, 2020
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Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
Hadi Salman, Greg Yang, Jerry Li, Pengchuan Zhang, Huan Zhang, Ilya Razenshteyn, Sebastien Bubeck
NeurIPS, 2019
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Equalized odds postprocessing under imperfect group information
Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern
arXiv, 2019
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Implicit bias of gradient descent on linear convolutional networks
Suriya Gun 2018asekar, Jason D. Lee, Daniel Soudry, Nathan Srebro
arXiv, 2019