Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Sherman, Uri"'
We study the generalization performance of gradient methods in the fundamental stochastic convex optimization setting, focusing on its dimension dependence. First, for full-batch gradient descent (GD) we give a construction of a learning problem in d
Externí odkaz:
http://arxiv.org/abs/2401.12058
We study regret minimization in online episodic linear Markov Decision Processes, and obtain rate-optimal $\widetilde O (\sqrt K)$ regret where $K$ denotes the number of episodes. Our work is the first to establish the optimal (w.r.t.~$K$) rate of co
Externí odkaz:
http://arxiv.org/abs/2308.14642
We study reinforcement learning with linear function approximation and adversarially changing cost functions, a setup that has mostly been considered under simplifying assumptions such as full information feedback or exploratory conditions.We present
Externí odkaz:
http://arxiv.org/abs/2301.13087
An abundance of recent impossibility results establish that regret minimization in Markov games with adversarial opponents is both statistically and computationally intractable. Nevertheless, none of these results preclude the possibility of regret m
Externí odkaz:
http://arxiv.org/abs/2207.14211
We study to what extent may stochastic gradient descent (SGD) be understood as a "conventional" learning rule that achieves generalization performance by obtaining a good fit to training data. We consider the fundamental stochastic convex optimizatio
Externí odkaz:
http://arxiv.org/abs/2202.13361
We study online convex optimization in the random order model, recently proposed by \citet{garber2020online}, where the loss functions may be chosen by an adversary, but are then presented to the online algorithm in a uniformly random order. Focusing
Externí odkaz:
http://arxiv.org/abs/2106.15207
Autor:
Sherman, Uri, Koren, Tomer
We study a variant of online convex optimization where the player is permitted to switch decisions at most $S$ times in expectation throughout $T$ rounds. Similar problems have been addressed in prior work for the discrete decision set setting, and m
Externí odkaz:
http://arxiv.org/abs/2102.03803