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ORCID34th ALT 2023: Singapore
- Shipra Agrawal, Francesco Orabona:
International Conference on Algorithmic Learning Theory, February 20-23, 2023, Singapore. Proceedings of Machine Learning Research 201, PMLR 2023 - Algorithmic Learning Theory 2023: Preface. 1-2
- Naman Agarwal, Brian Bullins, Karan Singh:
Variance-Reduced Conservative Policy Iteration. 3-33 - Maryam Aliakbarpour, Amartya Shankha Biswas, Kavya Ravichandran, Ronitt Rubinfeld:
Testing Tail Weight of a Distribution Via Hazard Rate. 34-81 - Eshwar Ram Arunachaleswaran, Anindya De, Sampath Kannan:
Reconstructing Ultrametric Trees from Noisy Experiments. 82-114 - Hassan Ashtiani, Vinayak Pathak, Ruth Urner:
Adversarially Robust Learning with Tolerance. 115-135 - Antoine Barrier, Aurélien Garivier, Gilles Stoltz:
On Best-Arm Identification with a Fixed Budget in Non-Parametric Multi-Armed Bandits. 136-181 - Robi Bhattacharjee, Max Hopkins, Akash Kumar, Hantao Yu, Kamalika Chaudhuri:
Robust Empirical Risk Minimization with Tolerance. 182-203 - Robi Bhattacharjee, Jacob Imola, Michal Moshkovitz, Sanjoy Dasgupta:
Online k-means Clustering on Arbitrary Data Streams. 204-236 - Oliver Biggar, Iman Shames:
The Replicator Dynamic, Chain Components and the Response Graph. 237-258 - Deeparnab Chakrabarty, Hang Liao:
A Query Algorithm for Learning a Spanning Forest in Weighted Undirected Graphs. 259-274 - Sabyasachi Chatterjee, Subhajit Goswami:
Spatially Adaptive Online Prediction of Piecewise Regular Functions. 275-309 - Liyu Chen, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric:
Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path. 310-357 - Sinho Chewi, Sébastien Bubeck, Adil Salim:
On the complexity of finding stationary points of smooth functions in one dimension. 358-374 - Sinho Chewi, Patrik Gerber, Holden Lee, Chen Lu:
Fisher information lower bounds for sampling. 375-410 - Julien Chhor, Flore Sentenac:
Robust Estimation of Discrete Distributions under Local Differential Privacy. 411-446 - Eugenio Clerico, George Deligiannidis, Arnaud Doucet:
Wide stochastic networks: Gaussian limit and PAC-Bayesian training. 447-470 - Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Pseudonorm Approachability and Applications to Regret Minimization. 471-509 - Christoph Dann, Chen-Yu Wei, Julian Zimmert:
A Unified Algorithm for Stochastic Path Problems. 510-557 - Jingqiu Ding, Yiding Hua:
SQ Lower Bounds for Random Sparse Planted Vector Problem. 558-596 - Feyza Duman Keles, Pruthuvi Mahesakya Wijewardena, Chinmay Hegde:
On The Computational Complexity of Self-Attention. 597-619 - Germano Gabbianelli, Gergely Neu, Matteo Papini:
Online Learning with Off-Policy Feedback. 620-641 - Sreenivas Gollapudi, Kostas Kollias, Chinmay Maheshwari
, Manxi Wu:
Online Learning for Traffic Navigation in Congested Networks. 642-662 - Mahdi Haghifam, Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund, Daniel M. Roy, Gintare Karolina Dziugaite:
Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization. 663-706 - Niki Hasrati, Shai Ben-David:
On Computable Online Learning. 707-725 - Junya Honda, Shinji Ito, Taira Tsuchiya:
Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems. 726-754 - Zeyu Jia, Randy Jia, Dhruv Madeka, Dean P. Foster:
Linear Reinforcement Learning with Ball Structure Action Space. 755-775 - Marc Jourdan, Rémy Degenne, Emilie Kaufmann:
Dealing with Unknown Variances in Best-Arm Identification. 776-849 - Anand Kalvit, Assaf Zeevi:
Complexity Analysis of a Countable-armed Bandit Problem. 850-890 - Eniko Kevi, Kim Thang Nguyen:
Primal-Dual Algorithms with Predictions for Online Bounded Allocation and Ad-Auctions Problems. 891-908 - Ivan Lau, Yan Hao Ling, Mayank Shrivastava, Jonathan Scarlett:
Max-Quantile Grouped Infinite-Arm Bandits. 909-945 - Holden Lee, Jianfeng Lu, Yixin Tan:
Convergence of score-based generative modeling for general data distributions. 946-985 - Andrew Lowy, Meisam Razaviyayn:
Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses. 986-1054 - Zhou Lu, Nataly Brukhim, Paula Gradu, Elad Hazan:
Projection-free Adaptive Regret with Membership Oracles. 1055-1073 - Haipeng Luo, Hanghang Tong, Mengxiao Zhang, Yuheng Zhang:
Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs. 1074-1100 - Gergely Neu, Nneka Okolo:
Efficient Global Planning in Large MDPs via Stochastic Primal-Dual Optimization. 1101-1123 - Quan Nguyen, Nishant A. Mehta:
Adversarial Online Multi-Task Reinforcement Learning. 1124-1165 - Aldo Pacchiano, Peter L. Bartlett, Michael I. Jordan:
An Instance-Dependent Analysis for the Cooperative Multi-Player Multi-Armed Bandit. 1166-1215 - Junhyung Park, Krikamol Muandet:
Towards Empirical Process Theory for Vector-Valued Functions: Metric Entropy of Smooth Function Classes. 1216-1260 - Stephen Pasteris:
Perceptronic Complexity and Online Matrix Completion. 1261-1291 - Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli:
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. 1292-1342 - El Mehdi Saad, Gilles Blanchard:
Constant regret for sequence prediction with limited advice. 1343-1386 - Seiyun Shin, Han Zhao, Ilan Shomorony:
Adaptive Power Method: Eigenvector Estimation from Sampled Data. 1387-1410 - Hans Ulrich Simon:
Tournaments, Johnson Graphs and NC-Teaching. 1411-1428 - Nadav Timor, Gal Vardi, Ohad Shamir:
Implicit Regularization Towards Rank Minimization in ReLU Networks. 1429-1459 - Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann:
Optimistic PAC Reinforcement Learning: the Instance-Dependent View. 1460-1480 - Chung-En Tsai, Hao-Chung Cheng, Yen-Huan Li:
Online Self-Concordant and Relatively Smooth Minimization, With Applications to Online Portfolio Selection and Learning Quantum States. 1481-1483 - Taira Tsuchiya, Shinji Ito, Junya Honda:
Best-of-Both-Worlds Algorithms for Partial Monitoring. 1484-1515 - Alexei Novikov, Stephen White:
Dictionary Learning for the Almost-Linear Sparsity Regime. 1516-1554 - Fan Zhou, Ping Li, Cun-Hui Zhang:
Universal Bias Reduction in Estimation of Smooth Additive Function in High Dimensions. 1555-1578
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