| 2021 | Uncertainty quantification using martingales for misspecified Gaussian processes. | Willie Neiswanger, Aaditya Ramdas |
| 2021 | Descent-to-Delete: Gradient-Based Methods for Machine Unlearning. | Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi |
| 2021 | Unexpected Effects of Online no-Substitution k-means Clustering. | Michal Moshkovitz |
| 2021 | Learning with Comparison Feedback: Online Estimation of Sample Statistics. | Michela Meister, Sloan Nietert |
| 2021 | Adaptive Reward-Free Exploration. | Emilie Kaufmann, Pierre Mnard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko |
| 2021 | Efficient Learning with Arbitrary Covariate Shift. | Adam Tauman Kalai, Varun Kanade |
| 2021 | Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback. | Marc Jourdan, Mojmr Mutn, Johannes Kirschner, Andreas Krause |
| 2021 | Characterizing the implicit bias via a primal-dual analysis. | Ziwei Ji, Matus Telgarsky |
| 2021 | Precise Minimax Regret for Logistic Regression with Categorical Feature Values. | Philippe Jacquet, Gil I. Shamir, Wojciech Szpankowski |
| 2021 | Submodular combinatorial information measures with applications in machine learning. | Rishabh K. Iyer, Ninad Khargoankar, Jeff A. Bilmes, Himanshu Asanani |
| 2021 | Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound. | Steve Hanneke, Aryeh Kontorovich |
| 2021 | Near-tight closure b ounds for the Littlestone and threshold dimensions. | Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi |
| 2021 | Subspace Embeddings under Nonlinear Transformations. | Aarshvi Gajjar, Cameron Musco |
| 2021 | A Technical Note on Non-Stationary Parametric Bandits: Existing Mistakes and Preliminary Solutions. | Louis Faury, Yoan Russac, Marc Abeille, Clment Calauznes |
| 2021 | Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds. | Ehsan Emamjomeh-Zadeh, Chen-Yu Wei, Haipeng Luo, David Kempe |
| 2021 | Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited. | Omar Darwiche Domingues, Pierre Mnard, Emilie Kaufmann, Michal Valko |
| 2021 | Last Round Convergence and No-Dynamic Regret in Asymmetric Repeated Games. | Le Cong Dinh, Tri-Dung Nguyen, Alain B. Zemkoho, Long Tran-Thanh |
| 2021 | Asymptotically Optimal Strategies For Combinatorial Semi-Bandits in Polynomial Time. | Thibaut Cuvelier, Richard Combes, Eric Gourdin |
| 2021 | Learning a mixture of two subspaces over finite fields. | Aidao Chen, Anindya De, Aravindan Vijayaraghavan |
| 2021 | Learning and Testing Irreducible Markov Chains via the k-Cover Time. | Siu On Chan, Qinghua Ding, Sing Hei Li |
| 2021 | Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics. | Mark Cesar, Ryan Rogers |
| 2021 | Online Boosting with Bandit Feedback. | Nataly Brukhim, Elad Hazan |
| 2021 | No-substitution k-means Clustering with Adversarial Order. | Robi Bhattacharjee, Michal Moshkovitz |
| 2021 | Sequential prediction under log-loss with side information. | Alankrita Bhatt, Young-Han Kim |
| 2021 | Stochastic Top-K Subset Bandits with Linear Space and Non-Linear Feedback. | Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn, Abhishek K. Umrawal |