Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret

25 February 2017

Papers citing "Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret"

11 / 11 papers shown

Title
Optimistic Information Directed Sampling Gergely Neu Matteo Papini Ludovic Schwartz 153 2 0 23 Feb 2024
Delaytron: Efficient Learning of Multiclass Classifiers with Delayed Bandit Feedbacks Naresh Manwani Mudit Agarwal 48 2 0 17 May 2022
Efficient Methods for Online Multiclass Logistic Regression Naman Agarwal Satyen Kale Julian Zimmert 123 12 0 06 Oct 2021
Beyond Bandit Feedback in Online Multiclass Classification Dirk van der Hoeven Federico Fusco Nicolò Cesa-Bianchi OffRL 79 13 0 07 Jun 2021
Exploiting the Surrogate Gap in Online Multiclass Classification Dirk van der Hoeven 81 10 0 24 Jul 2020
Efficient and Robust Algorithms for Adversarial Linear Contextual Bandits Gergely Neu Julia Olkhovskaya 188 49 0 01 Feb 2020
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case A. Beygelzimer D. Pál Balazs Szorenyi D. Thiruvenkatachari Chen-Yu Wei Chicheng Zhang 54 12 0 06 Feb 2019
Online Multiclass Classification Based on Prediction Margin for Partial Feedback Takuo Kaneko Issei Sato Masashi Sugiyama 67 12 0 04 Feb 2019
Online Multiclass Boosting with Bandit Feedback Daniel T. Zhang Young Hun Jung Ambuj Tewari 71 7 0 11 Oct 2018
Contextual bandits with surrogate losses: Margin bounds and efficient algorithms Dylan J. Foster A. Krishnamurthy 224 18 0 28 Jun 2018
Online Learning: A Comprehensive Survey Guosheng Lin Doyen Sahoo Jing Lu P. Zhao OffRL 169 695 0 08 Feb 2018