Fighting Bandits with a New Kind of Smoothness

Fighting Bandits with a New Kind of Smoothness

14 December 2015

Jacob D. Abernethy

Papers citing "Fighting Bandits with a New Kind of Smoothness"

16 / 16 papers shown

Title
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity Quan Nguyen Nishant A. Mehta Cristóbal Guzmán 39 1 0 01 Oct 2024
Optimism in the Face of Ambiguity Principle for Multi-Armed Bandits Mengmeng Li Daniel Kuhn Bahar Taşkesen 44 0 0 30 Sep 2024
Improved Regret Bounds for Bandits with Expert Advice Nicolò Cesa-Bianchi Khaled Eldowa Emmanuel Esposito Julia Olkhovskaya 38 0 0 24 Jun 2024
$A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $Θ(T^{2/3})$ and its Application to Best-of-Both-Worlds$ A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $Θ(T^{2/3})$ and its Application to Best-of-Both-Worlds Taira Tsuchiya Shinji Ito 26 0 0 30 May 2024
Distributed No-Regret Learning for Multi-Stage Systems with End-to-End Bandit Feedback I-Hong Hou OffRL 44 0 0 06 Apr 2024
A Best-of-both-worlds Algorithm for Bandits with Delayed Feedback with Robustness to Excessive Delays Saeed Masoudian Julian Zimmert Yevgeny Seldin 45 3 0 21 Aug 2023
Meta-Learning Adversarial Bandit Algorithms M. Khodak Ilya Osadchiy Keegan Harris Maria-Florina Balcan Kfir Y. Levy Ron Meir Zhiwei Steven Wu FedML 30 2 0 05 Jul 2023
On the Minimax Regret for Online Learning with Feedback Graphs Khaled Eldowa Emmanuel Esposito Tommaso Cesari Nicolò Cesa-Bianchi 33 8 0 24 May 2023
No-Regret Online Prediction with Strategic Experts Omid Sadeghi Maryam Fazel 43 1 0 24 May 2023
Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning Jiatai Huang Yan Dai Longbo Huang 27 6 0 25 Jan 2023
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits Jiatai Huang Yan Dai Longbo Huang 27 14 0 28 Jan 2022
Improved Analysis of the Tsallis-INF Algorithm in Stochastically Constrained Adversarial Bandits and Stochastic Bandits with Adversarial Corruptions Saeed Masoudian Yevgeny Seldin 22 14 0 23 Mar 2021
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously Julian Zimmert Haipeng Luo Chen-Yu Wei 11 79 0 25 Jan 2019
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits Julian Zimmert Yevgeny Seldin AAML 24 175 0 19 Jul 2018
Corralling a Band of Bandit Algorithms Alekh Agarwal Haipeng Luo Behnam Neyshabur Robert Schapire 30 154 0 19 Dec 2016
Prediction by Random-Walk Perturbation Luc Devroye Gábor Lugosi Gergely Neu 62 37 0 23 Feb 2013