Session 7 | 37th International Conference on Algorithmic Learning Theory (ALT 2026) and ShaiFest
Автор: Fields Institute
Загружено: 2026-02-26
Просмотров: 89
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[Wednesday, February 25, 2026]
Distribution-Dependent Rates for Multi-Distribution Learning - 00:00-10:17
(Rafael Hanashiro, Patrick Jaillet)
Bridging Lifelong and Multi-Task Representation Learning via Algorithm and Complexity Measure
(Zhi Wang, Chicheng Zhang, Ramya Korlakai Vinayak) - 10:20-20:45
Nearest Neighbours for Distribution Shift - 20:50-30:21
(Robi Bhattacharjee, Nick Ritter, and Kamalika Chaudhuri)
Efficient and Provable Algorithms for Covariate Shift - 30:22-40:38
(Deeksha Adil, Jaroslaw Blasiok)
Multi-distribution Learning: From Worst-Case Optimality to Lexicographic Min-Max Optimality - 40:39-50:40
(Guanghui Wang, Umar Syed, Robert E. Schapire, Jacob Abernethy)
PAC-Bayesian Analysis of the Surrogate Relation between Joint Embedding and Supervised Downstream Losses - 50:41-1:01:12
(Theresa Wasserer, Maximilian Fleissner, Debarghya Ghoshdastidar)
From Continual Learning to SGD and Back: Better Rates for Continual Linear Models - 1:01:13-1:11:06
(Itay Evron, Ran Levinstein, Matan Schliserman, Uri Sherman, Tomer Koren, Daniel Soudry, Nathan Srebro)
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