| 2021 | A Deep Conditioning Treatment of Neural Networks. Naman Agarwal, Pranjal Awasthi, Satyen Kale |
| 2021 | A Technical Note on Non-Stationary Parametric Bandits: Existing Mistakes and Preliminary Solutions. Louis Faury, Yoan Russac, Marc Abeille, Clément Calauzènes |
| 2021 | A case where a spindly two-layer linear network decisively outperforms any neural network with a fully connected input layer. Manfred K. Warmuth, Wojciech Kotlowski, Ehsan Amid |
| 2021 | Adaptive Reward-Free Exploration. Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko |
| 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 | Algorithmic Learning Theory 2021: Preface. |
| 2021 | Algorithmic Learning Theory, 16-19 March 2021, Virtual Conference, Worldwide. Vitaly Feldman, Katrina Ligett, Sivan Sabato |
| 2021 | An Efficient Algorithm for Cooperative Semi-Bandits. Riccardo Della Vecchia, Tommaso Cesari |
| 2021 | Asymptotically Optimal Strategies For Combinatorial Semi-Bandits in Polynomial Time. Thibaut Cuvelier, Richard Combes, Eric Gourdin |
| 2021 | Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance. Jie Shen, Chicheng Zhang |
| 2021 | Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics. Mark Cesar, Ryan Rogers |
| 2021 | Characterizing the implicit bias via a primal-dual analysis. Ziwei Ji, Matus Telgarsky |
| 2021 | Contrastive learning, multi-view redundancy, and linear models. Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu |
| 2021 | Descent-to-Delete: Gradient-Based Methods for Machine Unlearning. Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi |
| 2021 | Differentially Private Assouad, Fano, and Le Cam. Jayadev Acharya, Ziteng Sun, Huanyu Zhang |
| 2021 | Efficient Algorithms for Stochastic Repeated Second-price Auctions. Juliette Achddou, Olivier Cappé, Aurélien Garivier |
| 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, Mojmír Mutný, Johannes Kirschner, Andreas Krause |
| 2021 | Efficient sampling from the Bingham distribution. Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski |
| 2021 | Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited. Omar Darwiche Domingues, Pierre Ménard, Emilie Kaufmann, Michal Valko |
| 2021 | Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data. Di Wang, Huangyu Zhang, Marco Gaboardi, Jinhui Xu |
| 2021 | Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints. Jayadev Acharya, Peter Kairouz, Yuhan Liu, Ziteng Sun |
| 2021 | Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions. Gellért Weisz, Philip Amortila, Csaba Szepesvári |
| 2021 | Intervention Efficient Algorithms for Approximate Learning of Causal Graphs. Raghavendra Addanki, Andrew McGregor, Cameron Musco |
| 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 | Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization. Jacob D. Abernethy, Kevin A. Lai, Andre Wibisono |
| 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 | Learning with Comparison Feedback: Online Estimation of Sample Statistics. Michela Meister, Sloan Nietert |
| 2021 | Near-tight closure b ounds for the Littlestone and threshold dimensions. Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi |
| 2021 | No-substitution k-means Clustering with Adversarial Order. Robi Bhattacharjee, Michal Moshkovitz |
| 2021 | Non-uniform Consistency of Online Learning with Random Sampling. Changlong Wu, Narayana Santhanam |
| 2021 | On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians. Ishaq Aden-Ali, Hassan Ashtiani, Gautam Kamath |
| 2021 | Online Boosting with Bandit Feedback. Nataly Brukhim, Elad Hazan |
| 2021 | Online Learning of Facility Locations. Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster |
| 2021 | Precise Minimax Regret for Logistic Regression with Categorical Feature Values. Philippe Jacquet, Gil I. Shamir, Wojciech Szpankowski |
| 2021 | Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model. Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric |
| 2021 | Self-Tuning Bandits over Unknown Covariate-Shifts. Joseph Suk, Samory Kpotufe |
| 2021 | Sequential prediction under log-loss with side information. Alankrita Bhatt, Young-Han Kim |
| 2021 | Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound. Steve Hanneke, Aryeh Kontorovich |
| 2021 | Statistical guarantees for generative models without domination. Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak S. Dalalyan |
| 2021 | Stochastic Dueling Bandits with Adversarial Corruption. Arpit Agarwal, Shivani Agarwal, Prathamesh Patil |
| 2021 | Stochastic Top-K Subset Bandits with Linear Space and Non-Linear Feedback. Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn, Abhishek K. Umrawal |
| 2021 | Submodular combinatorial information measures with applications in machine learning. Rishabh K. Iyer, Ninad Khargoankar, Jeff A. Bilmes, Himanshu Asanani |
| 2021 | Subspace Embeddings under Nonlinear Transformations. Aarshvi Gajjar, Cameron Musco |
| 2021 | Testing Product Distributions: A Closer Look. Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, N. V. Vinodchandran |
| 2021 | Uncertainty quantification using martingales for misspecified Gaussian processes. Willie Neiswanger, Aaditya Ramdas |
| 2021 | Unexpected Effects of Online no-Substitution k-means Clustering. Michal Moshkovitz |