| 2023 | A Query Algorithm for Learning a Spanning Forest in Weighted Undirected Graphs. Deeparnab Chakrabarty, Hang Liao |
| 2023 | A Unified Algorithm for Stochastic Path Problems. Christoph Dann, Chen-Yu Wei, Julian Zimmert |
| 2023 | Adaptive Power Method: Eigenvector Estimation from Sampled Data. Seiyun Shin, Han Zhao, Ilan Shomorony |
| 2023 | Adversarial Online Multi-Task Reinforcement Learning. Quan Nguyen, Nishant A. Mehta |
| 2023 | Adversarially Robust Learning with Tolerance. Hassan Ashtiani, Vinayak Pathak, Ruth Urner |
| 2023 | Algorithmic Learning Theory 2023: Preface. |
| 2023 | Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli |
| 2023 | An Instance-Dependent Analysis for the Cooperative Multi-Player Multi-Armed Bandit. Aldo Pacchiano, Peter L. Bartlett, Michael I. Jordan |
| 2023 | Best-of-Both-Worlds Algorithms for Partial Monitoring. Taira Tsuchiya, Shinji Ito, Junya Honda |
| 2023 | Complexity Analysis of a Countable-armed Bandit Problem. Anand Kalvit, Assaf Zeevi |
| 2023 | Constant regret for sequence prediction with limited advice. El Mehdi Saad, Gilles Blanchard |
| 2023 | Convergence of score-based generative modeling for general data distributions. Holden Lee, Jianfeng Lu, Yixin Tan |
| 2023 | Dealing with Unknown Variances in Best-Arm Identification. Marc Jourdan, Rémy Degenne, Emilie Kaufmann |
| 2023 | Dictionary Learning for the Almost-Linear Sparsity Regime. Alexei Novikov, Stephen White |
| 2023 | Efficient Global Planning in Large MDPs via Stochastic Primal-Dual Optimization. Gergely Neu, Nneka Okolo |
| 2023 | Fisher information lower bounds for sampling. Sinho Chewi, Patrik Gerber, Holden Lee, Chen Lu |
| 2023 | Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems. Junya Honda, Shinji Ito, Taira Tsuchiya |
| 2023 | Implicit Regularization Towards Rank Minimization in ReLU Networks. Nadav Timor, Gal Vardi, Ohad Shamir |
| 2023 | Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs. Haipeng Luo, Hanghang Tong, Mengxiao Zhang, Yuheng Zhang |
| 2023 | International Conference on Algorithmic Learning Theory, February 20-23, 2023, Singapore. Shipra Agrawal, Francesco Orabona |
| 2023 | Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization. Mahdi Haghifam, Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund, Daniel M. Roy, Gintare Karolina Dziugaite |
| 2023 | Linear Reinforcement Learning with Ball Structure Action Space. Zeyu Jia, Randy Jia, Dhruv Madeka, Dean P. Foster |
| 2023 | Max-Quantile Grouped Infinite-Arm Bandits. Ivan Lau, Yan Hao Ling, Mayank Shrivastava, Jonathan Scarlett |
| 2023 | On Best-Arm Identification with a Fixed Budget in Non-Parametric Multi-Armed Bandits. Antoine Barrier, Aurélien Garivier, Gilles Stoltz |
| 2023 | On Computable Online Learning. Niki Hasrati, Shai Ben-David |
| 2023 | On The Computational Complexity of Self-Attention. Feyza Duman Keles, Pruthuvi Mahesakya Wijewardena, Chinmay Hegde |
| 2023 | On the complexity of finding stationary points of smooth functions in one dimension. Sinho Chewi, Sébastien Bubeck, Adil Salim |
| 2023 | Online Learning for Traffic Navigation in Congested Networks. Sreenivas Gollapudi, Kostas Kollias, Chinmay Maheshwari, Manxi Wu |
| 2023 | Online Learning with Off-Policy Feedback. Germano Gabbianelli, Gergely Neu, Matteo Papini |
| 2023 | Online Self-Concordant and Relatively Smooth Minimization, With Applications to Online Portfolio Selection and Learning Quantum States. Chung-En Tsai, Hao-Chung Cheng, Yen-Huan Li |
| 2023 | Online k-means Clustering on Arbitrary Data Streams. Robi Bhattacharjee, Jacob Imola, Michal Moshkovitz, Sanjoy Dasgupta |
| 2023 | Optimistic PAC Reinforcement Learning: the Instance-Dependent View. Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann |
| 2023 | Perceptronic Complexity and Online Matrix Completion. Stephen Pasteris |
| 2023 | Primal-Dual Algorithms with Predictions for Online Bounded Allocation and Ad-Auctions Problems. Eniko Kevi, Kim Thang Nguyen |
| 2023 | Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses. Andrew Lowy, Meisam Razaviyayn |
| 2023 | Projection-free Adaptive Regret with Membership Oracles. Zhou Lu, Nataly Brukhim, Paula Gradu, Elad Hazan |
| 2023 | Pseudonorm Approachability and Applications to Regret Minimization. Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan |
| 2023 | Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path. Liyu Chen, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric |
| 2023 | Reconstructing Ultrametric Trees from Noisy Experiments. Eshwar Ram Arunachaleswaran, Anindya De, Sampath Kannan |
| 2023 | Robust Empirical Risk Minimization with Tolerance. Robi Bhattacharjee, Max Hopkins, Akash Kumar, Hantao Yu, Kamalika Chaudhuri |
| 2023 | Robust Estimation of Discrete Distributions under Local Differential Privacy. Julien Chhor, Flore Sentenac |
| 2023 | SQ Lower Bounds for Random Sparse Planted Vector Problem. Jingqiu Ding, Yiding Hua |
| 2023 | Spatially Adaptive Online Prediction of Piecewise Regular Functions. Sabyasachi Chatterjee, Subhajit Goswami |
| 2023 | Testing Tail Weight of a Distribution Via Hazard Rate. Maryam Aliakbarpour, Amartya Shankha Biswas, Kavya Ravichandran, Ronitt Rubinfeld |
| 2023 | The Replicator Dynamic, Chain Components and the Response Graph. Oliver Biggar, Iman Shames |
| 2023 | Tournaments, Johnson Graphs and NC-Teaching. Hans Ulrich Simon |
| 2023 | Towards Empirical Process Theory for Vector-Valued Functions: Metric Entropy of Smooth Function Classes. Junhyung Park, Krikamol Muandet |
| 2023 | Universal Bias Reduction in Estimation of Smooth Additive Function in High Dimensions. Fan Zhou, Ping Li, Cun-Hui Zhang |
| 2023 | Variance-Reduced Conservative Policy Iteration. Naman Agarwal, Brian Bullins, Karan Singh |
| 2023 | Wide stochastic networks: Gaussian limit and PAC-Bayesian training. Eugenio Clerico, George Deligiannidis, Arnaud Doucet |