Improved Regret Bounds of (Multinomial) Logistic Bandits via
Regret-to-Confidence-Set Conversion

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Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion

28 October 2023

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Papers citing "Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion"

11 / 11 papers shown

Title
Linear Bandits with Non-i.i.d. Noise Baptiste Abeles Eugenio Clerico Hamish Flynn Gergely Neu 32 0 0 26 May 2025
Neural Logistic Bandits Seoungbin Bae Dabeen Lee 527 0 0 04 May 2025
Confidence Sequences for Generalized Linear Models via Regret Analysis Eugenio Clerico Hamish Flynn W. Kotłowski Gergely Neu 81 2 0 23 Apr 2025
Optimal Design for Reward Modeling in RLHF Antoine Scheid Etienne Boursier Alain Durmus Michael I. Jordan Pierre Ménard Eric Moulines Michal Valko OffRL 148 9 0 22 Oct 2024
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits Junghyun Lee Se-Young Yun Kwang-Sung Jun 197 6 0 19 Jul 2024
Bandits with Preference Feedback: A Stackelberg Game Perspective Barna Pásztor Parnian Kassraie Andreas Krause 75 4 0 24 Jun 2024
Nearly Minimax Optimal Regret for Multinomial Logistic Bandit Joongkyu Lee Min-hwan Oh 93 7 0 16 May 2024
Generalized Linear Bandits with Limited Adaptivity Ayush Sawarni Nirjhar Das Siddharth Barman Gaurav Sinha 191 5 0 10 Apr 2024
Tighter Confidence Bounds for Sequential Kernel Regression H. Flynn David Reeb 58 3 0 19 Mar 2024
Active Preference Optimization for Sample Efficient RLHF Nirjhar Das Souradip Chakraborty Aldo Pacchiano Sayak Ray Chowdhury 158 22 0 16 Feb 2024
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization Kwang-Sung Jun Jungtaek Kim 66 2 0 12 Feb 2024