Papers
316 papers found
A Unified Algorithm for Stochastic Path Problems
Christoph Dann, Chen-Yu Wei, Julian Zimmert
Best-of-Both-Worlds Algorithms for Partial Monitoring
Taira Tsuchiya, Shinji Ito, Junya Honda
Complexity Analysis of a Countable-armed Bandit Problem
Anand Kalvit, Assaf Zeevi
Constant regret for sequence prediction with limited advice
El Mehdi Saad, Gilles Blanchard
Convergence of score-based generative modeling for general data distributions
Holden Lee, Jianfeng Lu, Yixin Tan
Dealing with Unknown Variances in Best-Arm Identification
Marc Jourdan, Degenne Rémy, Kaufmann Emilie
Dictionary Learning for the Almost-Linear Sparsity Regime
Alexei Novikov, Stephen White
Efficient Global Planning in Large MDPs via Stochastic Primal-Dual Optimization
Gergely Neu, Nneka Okolo
Fisher information lower bounds for sampling
Sinho Chewi, Patrik Gerber, Holden Lee et al.
Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems
Junya Honda, Shinji Ito, Taira Tsuchiya
Implicit Regularization Towards Rank Minimization in ReLU Networks
Nadav Timor, Gal Vardi, Ohad Shamir
Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs
Haipeng Luo, Hanghang Tong, Mengxiao Zhang et al.
Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization
Mahdi Haghifam, Borja Rodríguez-Gálvez, Ragnar Thobaben et al.
Linear Reinforcement Learning with Ball Structure Action Space
Zeyu Jia, Randy Jia, Dhruv Madeka et al.
Max-Quantile Grouped Infinite-Arm Bandits
Ivan Lau, Yan Hao Ling, Mayank Shrivastava et al.
On Best-Arm Identification with a Fixed Budget in Non-Parametric Multi-Armed Bandits
Antoine Barrier, Aurélien Garivier, Gilles Stoltz
On Computable Online Learning
Niki Hasrati, Shai Ben-David
Online k-means Clustering on Arbitrary Data Streams
Robi Bhattacharjee, Jacob Imola, Michal Moshkovitz et al.
Online Learning for Traffic Navigation in Congested Networks
Sreenivas Gollapudi, Kostas Kollias, Chinmay Maheshwari et al.
Online Learning with Off-Policy Feedback
Germano Gabbianelli, Gergely Neu, Matteo Papini
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
On the complexity of finding stationary points of smooth functions in one dimension
Sinho Chewi, Sébastien Bubeck, Adil Salim
On The Computational Complexity of Self-Attention
Feyza Duman Keles, Pruthuvi Mahesakya Wijewardena, Chinmay Hegde
Optimistic PAC Reinforcement Learning: the Instance-Dependent View
Andrea Tirinzoni, Aymen Al-Marjani, Emilie Kaufmann
Perceptronic Complexity and Online Matrix Completion
Stephen Pasteris