Publication ChaCha for Online AutoML Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi 2021 International Conference on Machine Learning (ICML 2021) | July 2021 Video Github Project
Publication The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu 2021 International Conference on Machine Learning | July 2021
Publication Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui 2021 International Conference on Machine Learning (ICML) | July 2021
Publication Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain 2021 International Conference on Machine Learning | July 2021 Project Project
Publication Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective Dylan Foster, Alexander Rakhlin, David Simchi-Levi, Yunzong Xu 2021 Conference on Learning Theory | July 2021
Publication Benign Overfitting of Constant-Stepsize SGD for Linear Regression Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Sham Kakade 2021 Conference on Learning Theory | July 2021
Publication Confidence-Budget Matching for Sequential Budgeted Learning Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor International Conference on Machine Learning | July 2021
Publication Faster Kernel Matrix Algebra via Density Estimation Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner July 2021
Publication Batch optimization for DNA synthesis Konstantin Makarychev, Miklos Racz, Cyrus Rashtchian, Sergey Yekhanin International Symposium on Information Theory (ISIT) | July 2021 Project
Publication Universal Graph Compression: Stochastic Block Models Alankrita Bhatt, Ziao Wang, Chi Wang, Lele Wang International Symposium on Information Theory (ISIT 2021) | July 2021
Research
Research