Publications
VisualVoice: Audio-Visual Speech Separation with Cross-Modal Consistency
R. Gao and K. Grauman
CVPR, 2021
A Spectral Analysis of Dot-product Kernels
Meyer Scetbon, Zaid Harchaoui
AISTATS, 2021
A Superquantile Approach for Federated Learning with Heterogeneous Devices
Y. Laguel, K. Pillutla, J. Malick, Z. Harchaoui
CISS, 2021
Improved Graph Clustering
Yudong Chen, Sujay Sanghavi, Huan Xu
arXiv, 2021
Something New Versus Tried and True: Ensuring 'Innovative' AI is 'Good' AI
Stephen C. Slota, Kenneth R. Fleischmann, Sherri Greenberg, Nitin Verma, Brenna Cummings, Lan Li, Chris Shenefiel
Few-Shot Learning via Learning the Representation, Provably
Simon S. Du, Wei Hu, Sham M. Kakade, Jason D. Lee, Qi Lei
ICLR, 2021
Scalable Multiagent Driving Policies For Reducing Traffic Congestion.
Jiaxun Cui, William Macke, Harel Yedidsion, Aastha Goyal, Daniel Urieli, and Peter Stone
AAMAS, 2021
Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm
Meena Jagadeesan, Ilya Razenshteyn, Suriya Gunasekar
arXiv, 2021
Learning to Improve Multi-Robot Hallway Navigation
Jin-Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone
CoRL, 2020
Entanglement is Necessary for Optimal Quantum Property Testing
Sebastien Bubeck, Sitan Chen, Jerry Li
arXiv, 2020
Adaptive Sampling to Reduce Disparate Performance
Jacob Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Jie (Claire) Zhang
arXiv, 2020
Value Alignment Verification
Daniel S. Brown, Jordan Schneioder, Scott Niekum
NeurIPS, 2020
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent.
Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam Klivans
ICML, 2020
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
RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration
Brahma Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, and Peter Stone
IROS, 2020
Reducing Sampling Error in Batch Temporal Difference Learning
Brahma Pavse, Ishan Durugkar, Josiah Hanna, and Peter Stone
ICML, 2020
The EMPATHIC Framework for Task Learning from Implicit Human Feedback
Yuchen Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox
CRL, 2020
On Sampling Error in Batch Action-Value Prediction Algorithms
Brahma S. Pavse, Josiah P. Hanna, Ishan Durugkar, and Peter Stone
NeurIPS, 2020