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Editors: Vitaly Feldman, Katrina Ligett, Sivan Sabato
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Algorithmic Learning Theory 2021: Preface
; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1-2
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Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization
Jacob Abernethy, Kevin A. Lai, Andre Wibisono; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:3-47
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Differentially Private Assouad, Fano, and Le Cam
Jayadev Acharya, Ziteng Sun, Huanyu Zhang; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:48-78
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Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints
Jayadev Acharya, Peter Kairouz, Yuhan Liu, Ziteng Sun; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:79-98
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Efficient Algorithms for Stochastic Repeated Second-price Auctions
Juliette Achddou, Olivier Cappé, Aurélien Garivier; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:99-150
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Intervention Efficient Algorithms for Approximate Learning of Causal Graphs
Raghavendra Addanki, Andrew McGregor, Cameron Musco; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:151-184
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On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians
Ishaq Aden-Ali, Hassan Ashtiani, Gautam Kamath; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:185-216
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Stochastic Dueling Bandits with Adversarial Corruption
Arpit Agarwal, Shivani Agarwal, Prathamesh Patil; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:217-248
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A Deep Conditioning Treatment of Neural Networks
Naman Agarwal, Pranjal Awasthi, Satyen Kale; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:249-305
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Stochastic Top-$K$ Subset Bandits with Linear Space and Non-Linear Feedback
Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn, Abhishek K. Umrawal; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:306-339
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Sequential prediction under log-loss with side information
Alankrita Bhatt, Young-Han Kim; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:340-344
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No-substitution k-means Clustering with Adversarial Order
Robi Bhattacharjee, Michal Moshkovitz; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:345-366
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Testing Product Distributions: A Closer Look
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, N. V. Vinodchandran; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:367-396
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Online Boosting with Bandit Feedback
Nataly Brukhim, Elad Hazan; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:397-420
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Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics
Mark Cesar, Ryan Rogers; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:421-457
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Learning and Testing Irreducible Markov Chains via the $k$-Cover Time
Siu On Chan, Qinghua Ding, Sing Hei Li; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:458-480
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Learning a mixture of two subspaces over finite fields
Aidao Chen, Anindya De, Aravindan Vijayaraghavan; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:481-504
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Asymptotically Optimal Strategies For Combinatorial Semi-Bandits in Polynomial Time
Thibaut Cuvelier, Richard Combes, Eric Gourdin; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:505-528
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An Efficient Algorithm for Cooperative Semi-Bandits
Riccardo Della Vecchia, Tommaso Cesari; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:529-552
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Last Round Convergence and No-Dynamic Regret in Asymmetric Repeated Games
Le Cong Dinh, Tri-Dung Nguyen, Alain B. Zemhoho, Long Tran-Thanh; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:553-577
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Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited
Omar Darwiche Domingues, Pierre Ménard, Emilie Kaufmann, Michal Valko; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:578-598
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Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds
Ehsan Emamjomeh-Zadeh, Chen-Yu Wei, Haipeng Luo, David Kempe; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:599-618
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A Technical Note on Non-Stationary Parametric Bandits: Existing Mistakes and Preliminary Solutions
Louis Faury, Yoan Russac, Marc Abeille, Clément Calauzènes; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:619-626
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Subspace Embeddings under Nonlinear Transformations
Aarshvi Gajjar, Cameron Musco; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:656-672
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Efficient sampling from the Bingham distribution
Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:673-685
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Near-tight Closure Bounds for the Littlestone and Threshold Dimensions
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:686-696
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Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound
Steve Hanneke, Aryeh Kontorovich; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:697-721
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Submodular combinatorial information measures with applications in machine learning
Rishabh Iyer, Ninad Khargoankar, Jeff Bilmes, Himanshu Asanani; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:722-754
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Precise Minimax Regret for Logistic Regression with Categorical Feature Values
Philippe Jacquet, Gil Shamir, Wojciech Szpankowski; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:755-771
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Characterizing the implicit bias via a primal-dual analysis
Ziwei Ji, Matus Telgarsky; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:772-804
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Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback
Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:805-849
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Efficient Learning with Arbitrary Covariate Shift
Adam Tauman Kalai, Varun Kanade; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:850-864
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Adaptive Reward-Free Exploration
Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:865-891
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Unexpected Effects of Online no-Substitution $k$-means Clustering
Michal Moshkovitz; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:892-930
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Descent-to-Delete: Gradient-Based Methods for Machine Unlearning
Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:931-962
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Uncertainty quantification using martingales for misspecified Gaussian processes
Willie Neiswanger, Aaditya Ramdas; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:963-982
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Learning with Comparison Feedback: Online Estimation of Sample Statistics
Michela Meister, Sloan Nietert; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:983-1001
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Online Learning of Facility Locations
Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1002-1050
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Statistical guarantees for generative models without domination
Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak Dalalyan; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1051-1071
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Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance
Jie Shen, Chicheng Zhang; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1072-1113
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Self-Tuning Bandits over Unknown Covariate-Shifts
Joseph Suk, Samory Kpotufe; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1114-1156
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Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model
Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1157-1178
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Contrastive learning, multi-view redundancy, and linear models
Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1179-1206
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Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data
Di Wang, Huangyu Zhang, Marco Gaboardi, Jinhui Xu; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1207-1213
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A case where a spindly two-layer linear network decisively outperforms any neural network with a fully connected input layer
Manfred K. Warmuth, Wojciech Kotłowski, Ehsan Amid; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1214-1236
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Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions
Gellért Weisz, Philip Amortila, Csaba Szepesvári; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1237-1264
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Non-uniform Consistency of Online Learning with Random Sampling
Changlong Wu, Narayana Santhanam; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1265-1285
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