| 2022 | A Model Selection Approach for Corruption Robust Reinforcement Learning. Chen-Yu Wei, Christoph Dann, Julian Zimmert |
| 2022 | Adversarial Interpretation of Bayesian Inference. Hisham Husain, Jeremias Knoblauch |
| 2022 | Algorithmic Learning Theory 2022: Preface. |
| 2022 | Algorithms for learning a mixture of linear classifiers. Aidao Chen, Anindya De, Aravindan Vijayaraghavan |
| 2022 | Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games. Zixiang Chen, Dongruo Zhou, Quanquan Gu |
| 2022 | Asymptotic Degradation of Linear Regression Estimates with Strategic Data Sources. Benjamin Roussillon, Nicolas Gast, Patrick Loiseau, Panayotis Mertikopoulos |
| 2022 | Beyond Bernoulli: Generating Random Outcomes that cannot be Distinguished from Nature. Cynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum, Gal Yona |
| 2022 | Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure. Hsu Kao, Chen-Yu Wei, Vijay G. Subramanian |
| 2022 | Distinguishing Relational Pattern Languages With a Small Number of Short Strings. Robert C. Holte, S. Mahmoud Mousawi, Sandra Zilles |
| 2022 | Distributed Online Learning for Joint Regret with Communication Constraints. Dirk van der Hoeven, Hédi Hadiji, Tim van Erven |
| 2022 | Efficient Methods for Online Multiclass Logistic Regression. Naman Agarwal, Satyen Kale, Julian Zimmert |
| 2022 | Efficient and Optimal Algorithms for Contextual Dueling Bandits under Realizability. Aadirupa Saha, Akshay Krishnamurthy |
| 2022 | Efficient and Optimal Fixed-Time Regret with Two Experts. Laura Greenstreet, Nicholas J. A. Harvey, Victor Sanches Portella |
| 2022 | Efficient local planning with linear function approximation. Dong Yin, Botao Hao, Yasin Abbasi-Yadkori, Nevena Lazic, Csaba Szepesvári |
| 2022 | Faster Noisy Power Method. Zhiqiang Xu, Ping Li |
| 2022 | Faster Perturbed Stochastic Gradient Methods for Finding Local Minima. Zixiang Chen, Dongruo Zhou, Quanquan Gu |
| 2022 | Faster Rates of Private Stochastic Convex Optimization. Jinyan Su, Lijie Hu, Di Wang |
| 2022 | Global Riemannian Acceleration in Hyperbolic and Spherical Spaces. David Martínez-Rubio |
| 2022 | Implicit Parameter-free Online Learning with Truncated Linear Models. Keyi Chen, Ashok Cutkosky, Francesco Orabona |
| 2022 | Improved rates for prediction and identification of partially observed linear dynamical systems. Holden Lee |
| 2022 | Inductive Bias of Gradient Descent for Weight Normalized Smooth Homogeneous Neural Nets. Depen Morwani, Harish G. Ramaswamy |
| 2022 | Infinitely Divisible Noise in the Low Privacy Regime. Rasmus Pagh, Nina Mesing Stausholm |
| 2022 | International Conference on Algorithmic Learning Theory, 29 March - 1 April 2022, Paris, France. Sanjoy Dasgupta, Nika Haghtalab |
| 2022 | Iterated Vector Fields and Conservatism, with Applications to Federated Learning. Zachary Charles, Keith Rush |
| 2022 | Learning what to remember. Robi Bhattacharjee, Gaurav Mahajan |
| 2022 | Learning with Distributional Inverters. Eric Binnendyk, Marco Carmosino, Antonina Kolokolova, R. Ramyaa, Manuel Sabin |
| 2022 | Leveraging Initial Hints for Free in Stochastic Linear Bandits. Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Qiuyi (Richard) Zhang |
| 2022 | Limiting Behaviors of Nonconvex-Nonconcave Minimax Optimization via Continuous-Time Systems. Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab S. Mirrokni |
| 2022 | Lower Bounds on the Total Variation Distance Between Mixtures of Two Gaussians. Sami Davies, Arya Mazumdar, Soumyabrata Pal, Cyrus Rashtchian |
| 2022 | Metric Entropy Duality and the Sample Complexity of Outcome Indistinguishability. Lunjia Hu, Charlotte Peale, Omer Reingold |
| 2022 | Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems. Belhal Karimi, Hoi-To Wai, Eric Moulines, Ping Li |
| 2022 | Multicalibrated Partitions for Importance Weights. Parikshit Gopalan, Omer Reingold, Vatsal Sharan, Udi Wieder |
| 2022 | On the Initialization for Convex-Concave Min-max Problems. Mingrui Liu, Francesco Orabona |
| 2022 | On the Last Iterate Convergence of Momentum Methods. Xiaoyu Li, Mingrui Liu, Francesco Orabona |
| 2022 | Polynomial-Time Sum-of-Squares Can Robustly Estimate Mean and Covariance of Gaussians Optimally. Pravesh K. Kothari, Peter Manohar, Brian Hu Zhang |
| 2022 | Privacy Amplification via Shuffling for Linear Contextual Bandits. Evrard Garcelon, Kamalika Chaudhuri, Vianney Perchet, Matteo Pirotta |
| 2022 | Refined Lower Bounds for Nearest Neighbor Condensation. Rajesh Chitnis |
| 2022 | Scale-Free Adversarial Multi Armed Bandits. Sudeep Raja Putta, Shipra Agrawal |
| 2022 | Social Learning in Non-Stationary Environments. Etienne Boursier, Vianney Perchet, Marco Scarsini |
| 2022 | TensorPlan and the Few Actions Lower Bound for Planning in MDPs under Linear Realizability of Optimal Value Functions. Gellért Weisz, Csaba Szepesvári, András György |
| 2022 | The Mirror Langevin Algorithm Converges with Vanishing Bias. Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono |
| 2022 | Understanding Simultaneous Train and Test Robustness. Pranjal Awasthi, Sivaraman Balakrishnan, Aravindan Vijayaraghavan |
| 2022 | Universal Online Learning with Unbounded Losses: Memory Is All You Need. Moïse Blanchard, Romain Cosson, Steve Hanneke |
| 2022 | Universally Consistent Online Learning with Arbitrarily Dependent Responses. Steve Hanneke |