Improved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits

23 November 2020

Papers citing "Improved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits"

10 / 10 papers shown

Title
Neural Logistic Bandits Seoungbin Bae Dabeen Lee 255 0 0 04 May 2025
Enhancing Preference-based Linear Bandits via Human Response Time Shen Li Yuyang Zhang Zhaolin Ren Claire Liang Na Li J. Shah 42 0 0 03 Jan 2025
Near Optimal Pure Exploration in Logistic Bandits Eduardo Ochoa Rivera Ambuj Tewari 30 0 0 28 Oct 2024
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits Junghyun Lee Se-Young Yun Kwang-Sung Jun 45 4 0 19 Jul 2024
Active Preference Learning for Ordering Items In- and Out-of-sample Herman Bergström Emil Carlsson Devdatt Dubhashi Fredrik D. Johansson 52 0 0 05 May 2024
One for All: Simultaneous Metric and Preference Learning over Multiple Users Gregory H. Canal Blake Mason Ramya Korlakai Vinayak R. Nowak FedML 19 11 0 07 Jul 2022
An Experimental Design Approach for Regret Minimization in Logistic Bandits Blake Mason Kwang-Sung Jun Lalit P. Jain 34 10 0 04 Feb 2022
Jointly Efficient and Optimal Algorithms for Logistic Bandits Louis Faury Marc Abeille Kwang-Sung Jun Clément Calauzènes 30 19 0 06 Jan 2022
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification James A. Grant David S. Leslie 50 3 0 29 Sep 2021
Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits Marc Abeille Louis Faury Clément Calauzènes 96 37 0 23 Oct 2020