Warm-starting Contextual Bandits: Robustly Combining Supervised and
Bandit Feedback

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Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback

2 January 2019

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Papers citing "Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback"

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Title
Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis Ruiquan Huang Donghao Li Chengshuai Shi Cong Shen Jing Yang OffRL 174 0 0 01 Jul 2025
Multi-Armed Bandits With Machine Learning-Generated Surrogate Rewards Wenlong Ji Yihan Pan Ruihao Zhu Lihua Lei 72 1 0 20 Jun 2025
Best Arm Identification with Possibly Biased Offline Data Le Yang Vincent Y. F. Tan Wang Chi Cheung 91 1 0 29 May 2025
Deconfounded Warm-Start Thompson Sampling with Applications to Precision Medicine Prateek Jaiswal Esmaeil Keyvanshokooh Junyu Cao 115 0 0 22 May 2025
Warm Starting of CMA-ES for Contextual Optimization Problems Yuta Sekino Kento Uchida Shinichi Shirakawa 188 0 0 18 Feb 2025
Online Bandit Learning with Offline Preference Data for Improved RLHF Akhil Agnihotri Rahul Jain Deepak Ramachandran Zheng Wen OffRL 304 3 0 13 Jun 2024
Leveraging User-Triggered Supervision in Contextual Bandits Alekh Agarwal Claudio Gentile T. V. Marinov 61 0 0 07 Feb 2023
Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in Bandits Siddhartha Banerjee Sean R. Sinclair Milind Tambe Lily Xu Chao Yu AI4TS 268 8 0 30 Sep 2022
Thompson Sampling for Robust Transfer in Multi-Task Bandits Zhi Wang Chicheng Zhang Kamalika Chaudhuri AAML 96 7 0 17 Jun 2022
Multitask Bandit Learning Through Heterogeneous Feedback Aggregation Zhi Wang Chicheng Zhang Manish Singh L. Riek Kamalika Chaudhuri 194 25 0 29 Oct 2020
Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decision Li Ye Yishi Lin Hong Xie John C. S. Lui CML 115 12 0 16 Jan 2020