-
16:10
Research on the combination of Top-K and Perm-K gradient sparsification algorithms for distributed setting
-
Timur Kharisov
(Moscow Institute of Physics and Technology)
-
16:25
Research on the combination of Top-K and Perm-K gradient sparsification algorithms for distributed setting
-
Кирилл Ачарйа
(МФТИ)
-
16:40
Анализ смещения распределений в контрастивном обучении / Mitigating Distributional Biases in Contrastive Learning
-
Лидия Троешестова
(Московский физико-технический институт)
-
16:55
ActSRF: How to segment images with uncertainty
-
Vsevolod Skorokhodov
(MIPT)
-
17:10
Using medium-sized language models to solve and formalize mathematical problems
-
Vasily Nesterov
(Moscow Institute of Physics and Technology)
-
17:25
Меры близости в задачах self-supervised learning
-
Andrew Vidanov
(MIPT)
