1 citations · 3 across the 4 of their papers we have counts for
4 papers
Sharp Optimal Algorithm for Derivative-Free Stochastic Convex Optimization in One Dimension
Alexandra Carpentier, Chloé Rouyer, Alexandre Tsybakov +1
Stochastic convex optimization is a classical problem with well-understood guarantees under first-order feedback. In contrast, for zero-order optimization with noisy function evalu…
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions
Tiancheng Jin, Junyan Liu, Chloé Rouyer +3
Existing online learning algorithms for adversarial Markov Decision Processes achieve regret after rounds of interactions even if the loss functions are chosen…
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs
Chloé Rouyer, Dirk van der Hoeven, Nicolò Cesa-Bianchi +1
We consider online learning with feedback graphs, a sequential decision-making framework where the learner's feedback is determined by a directed graph over the action set. We pres…
An Algorithm for Stochastic and Adversarial Bandits with Switching Costs
Chloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi
We propose an algorithm for stochastic and adversarial multiarmed bandits with switching costs, where the algorithm pays a price every time it switches the arm being played. Ou…