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1709.03163
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Variational inference for the multi-armed contextual bandit
10 September 2017
Iñigo Urteaga
C. Wiggins
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Papers citing
"Variational inference for the multi-armed contextual bandit"
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EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning
Asian Conference on Machine Learning (ACML), 2025
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Dixant Mittal
Wee Sun Lee
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0
17 Jan 2025
Stabilizing the Kumaraswamy Distribution
Max Wasserman
Gonzalo Mateos
BDL
220
4
0
01 Oct 2024
Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits
Ziyi Huang
Henry Lam
Haofeng Zhang
383
1
0
20 Jun 2024
Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits
Nicolas Nguyen
Imad Aouali
András Gyorgy
Claire Vernade
296
2
0
08 Feb 2024
Improving sample efficiency of high dimensional Bayesian optimization with MCMC
Zeji Yi
Yunyue Wei
Chu Xin Cheng
Kaibo He
Yanan Sui
197
8
0
05 Jan 2024
VITS : Variational Inference Thompson Sampling for contextual bandits
International Conference on Machine Learning (ICML), 2023
Pierre Clavier
Tom Huix
Alain Durmus
369
6
0
19 Jul 2023
Multiplier Bootstrap-based Exploration
International Conference on Machine Learning (ICML), 2023
Runzhe Wan
Haoyu Wei
Branislav Kveton
R. Song
201
3
0
03 Feb 2023
Mixed-Effect Thompson Sampling
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Imad Aouali
Branislav Kveton
S. Katariya
OffRL
352
14
0
30 May 2022
Multi-armed bandits for resource efficient, online optimization of language model pre-training: the use case of dynamic masking
Annual Meeting of the Association for Computational Linguistics (ACL), 2022
Iñigo Urteaga
Moulay Draidia
Tomer Lancewicki
Shahram Khadivi
AI4CE
216
1
0
24 Mar 2022
An Analysis of Ensemble Sampling
Neural Information Processing Systems (NeurIPS), 2022
Chao Qin
Zheng Wen
Xiuyuan Lu
Benjamin Van Roy
381
25
0
02 Mar 2022
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network
Yun-Da Tsai
Shou-De Lin
176
6
0
17 Feb 2022
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework
Neural Information Processing Systems (NeurIPS), 2022
Ziyi Huang
Henry Lam
A. Meisami
Haofeng Zhang
366
4
0
31 Jan 2022
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification
James A. Grant
David S. Leslie
246
4
0
29 Sep 2021
Thompson Sampling with a Mixture Prior
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Joey Hong
Branislav Kveton
Manzil Zaheer
Mohammad Ghavamzadeh
Craig Boutilier
249
14
0
10 Jun 2021
Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems
International Conference on Machine Learning (ICML), 2020
Tong Yu
Branislav Kveton
Zheng Wen
Ruiyi Zhang
Ole J. Mengshoel
TDI
200
2
0
09 Jul 2020
On Thompson Sampling with Langevin Algorithms
International Conference on Machine Learning (ICML), 2020
Eric Mazumdar
Aldo Pacchiano
Yi-An Ma
Peter L. Bartlett
Sai Li
251
12
0
23 Feb 2020
On Thompson Sampling for Smoother-than-Lipschitz Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
James A. Grant
David S. Leslie
285
6
0
08 Jan 2020
Thompson Sampling with Approximate Inference
My Phan
Yasin Abbasi-Yadkori
Justin Domke
151
29
0
14 Aug 2019
Scalable Thompson Sampling via Optimal Transport
Ruiyi Zhang
Zheng Wen
Changyou Chen
Lawrence Carin
OT
212
20
0
19 Feb 2019
Thompson Sampling for Noncompliant Bandits
Andrew Stirn
Tony Jebara
83
6
0
03 Dec 2018
Nonparametric Gaussian Mixture Models for the Multi-Armed Bandit
Iñigo Urteaga
C. Wiggins
294
3
0
08 Aug 2018
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