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NeurIPS 2022

36th Conference on Neural Information processing Systems

List of papers by ASSET researchers:

  1. Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints; Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani
  2. Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds; Aritra Mitra, Arman Adibi, George J. Pappas, Hamed Hassani
  3. Estimation of Entropy in Constant Space with Improved Sample Complexity; Maryam Aliakbarpour, Andrew McGregor, Jelani Nelson, Erik Waingarten
  4. Fair Bayes-Optimal Classifiers Under Predictive Parity; Xianli Zeng, Edgar Dobriban, Guang Cheng
  5. FedAvg with Fine Tuning: Local Updates Lead to Representation Learning; Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
  6. Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression; Liangzu Peng, Christian Kümmerle, Rene Vidal
  7. Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit; Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, eran malach, Cyril Zhang
  8. Neurosymbolic Deep Generative Models for Sequence Data with Relational Constraints; Halley Young, Maxwell Du, Osbert Bastani
  9. Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression; Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani
  10. Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications; Daniel Lee, Georgy Noarov, Mallesh Pai, Aaron Roth
  11. PAC Prediction Sets for Meta-Learning; Sangdon Park, Edgar Dobriban, Insup Lee, Osbert Bastani
  12. Practical Adversarial Multivalid Conformal Prediction; Osbert Bastani, Varun Gupta, Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth
  13. Private Synthetic Data for Multitask Learning and Marginal Queries; Giuseppe Vietri, Cedric Archambeau, Sergul Aydore, William Brown, Michael Kearns, Aaron Roth, Ankit Siva, Shuai Tang, Steven Wu
  14. Probable Domain Generalization via Quantile Risk Minimization; Cian Eastwood, Alexander Robey, Shashank Singh, Julius Von Kügelgen, Hamed Hassani, George J. Pappas, Bernhard Schölkopf
  15. Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms; Surbhi Goel, Sham M. Kakade, Adam Tauman Kalai, Cyril Zhang
  16. Regret Bounds for Risk-Sensitive Reinforcement Learning; Osbert Bastani, Yecheng Jason Ma, Estelle Shen, Wanqiao Xu
  17. TaSIL: Taylor Series Imitation Learning; Daniel Pfrommer, Thomas TCK Zhang, Stephen Tu, Nikolai Matni
  18. The alignment property of SGD noise and how it helps select flat minima: A stability analysis; Lei Wu, Mingze Wang, Weijie J Su