Publication Adversarial Dueling Bandits Aadirupa Saha, Tomer Koren, Yishay Mansour International Conference on Machine Learning | July 2021
Publication Correlation Clustering in Constant Many Parallel Rounds Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski 2021 International Conference on Machine Learning | July 2021
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 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 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 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 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 Confidence-Budget Matching for Sequential Budgeted Learning Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor International Conference on Machine Learning | July 2021
Publication Dueling Convex Optimization Aadirupa Saha, Tomer Koren, Yishay Mansour International Conference on Machine Learning | July 2021
