28 citations · 29 across the 11 of their papers we have counts for
8 papers · 1 filter
Minimax-optimal Halpern iterations for Lipschitz maps
Mario Bravo, Roberto Cominetti, Jongmin Lee
This paper investigates the minimax-optimality of Halpern fixed-point iterations for Lipschitz maps in general normed spaces. Starting from an a priori bound on the orbit of iterat…
Near-Optimal Sample Complexity for MDPs via Anchoring
Jongmin Lee, Mario Bravo, Roberto Cominetti
We study a new model-free algorithm to compute -optimal policies for average reward Markov decision processes, in the weakly communicating case. Given a generative mod…
Stochastic Halpern iteration in normed spaces and applications to reinforcement learning
Mario Bravo, Juan Pablo Contreras
We analyze the oracle complexity of the stochastic Halpern iteration with minibatch, where we aim to approximate fixed-points of nonexpansive and contractive operators in a normed…
Stochastic fixed-point iterations for nonexpansive maps: Convergence and error bounds
Mario Bravo, Roberto Cominetti
We study a stochastically perturbed version of the well-known Krasnoselski--Mann iteration for computing fixed points of nonexpansive maps in finite dimensional normed spaces. We d…
Universal bounds for fixed point iterations via optimal transport metrics
Mario Bravo, Thierry Champion, Roberto Cominetti
We present a self-contained analysis of a particular family of metrics over the set of non-negative integers. We show that these metrics, which are defined through a nested sequenc…
Rates of convergence for inexact Krasnosel'skii-Mann iterations in Banach spaces
Mario Bravo, Roberto Cominetti, Matías Pavez-Signé
We study the convergence of an inexact version of the classical Krasnosel'skii-Mann iteration for computing fixed points of nonexpansive maps. Our main result establishes a new met…
Sharp convergence rates for averaged nonexpansive maps
Mario Bravo, Roberto Cominetti
We establish sharp estimates for the convergence rate of the Kranosel'ski\vı-Mann fixed point iteration in general normed spaces, and we use them to show that the asymptotic regula…
On the robustness of learning in games with stochastically perturbed payoff observations
Mario Bravo, Panayotis Mertikopoulos
Motivated by the scarcity of accurate payoff feedback in practical applications of game theory, we examine a class of learning dynamics where players adjust their choices based on…