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Information Directed Sampling for Sparse Linear Bandits

Information Directed Sampling for Sparse Linear Bandits

29 May 2021
Botao Hao
Tor Lattimore
Wei Deng
ArXivPDFHTML

Papers citing "Information Directed Sampling for Sparse Linear Bandits"

32 / 32 papers shown
Title
On Bits and Bandits: Quantifying the Regret-Information Trade-off
On Bits and Bandits: Quantifying the Regret-Information Trade-off
Itai Shufaro
Nadav Merlis
Nir Weinberger
Shie Mannor
135
0
0
26 May 2024
Reinforcement Learning, Bit by Bit
Reinforcement Learning, Bit by Bit
Xiuyuan Lu
Benjamin Van Roy
Vikranth Dwaracherla
M. Ibrahimi
Ian Osband
Zheng Wen
44
70
0
06 Mar 2021
Asymptotically Optimal Information-Directed Sampling
Asymptotically Optimal Information-Directed Sampling
Johannes Kirschner
Tor Lattimore
Claire Vernade
Csaba Szepesvári
90
34
0
11 Nov 2020
High-Dimensional Sparse Linear Bandits
High-Dimensional Sparse Linear Bandits
Botao Hao
Tor Lattimore
Mengdi Wang
67
62
0
08 Nov 2020
Online Sparse Reinforcement Learning
Online Sparse Reinforcement Learning
Botao Hao
Tor Lattimore
Csaba Szepesvári
Mengdi Wang
OffRL
65
29
0
08 Nov 2020
Mirror Descent and the Information Ratio
Mirror Descent and the Information Ratio
Tor Lattimore
András Gyorgy
38
42
0
25 Sep 2020
Nearly Dimension-Independent Sparse Linear Bandit over Small Action
  Spaces via Best Subset Selection
Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection
Yining Wang
Yi Chen
Ethan X. Fang
Zhaoran Wang
Runze Li
104
16
0
04 Sep 2020
Dynamic Batch Learning in High-Dimensional Sparse Linear Contextual
  Bandits
Dynamic Batch Learning in High-Dimensional Sparse Linear Contextual Bandits
Zhimei Ren
Zhengyuan Zhou
52
31
0
27 Aug 2020
Sparsity-Agnostic Lasso Bandit
Sparsity-Agnostic Lasso Bandit
Min Hwan Oh
G. Iyengar
A. Zeevi
43
45
0
16 Jul 2020
Bypassing the Monster: A Faster and Simpler Optimal Algorithm for
  Contextual Bandits under Realizability
Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits under Realizability
D. Simchi-Levi
Yunzong Xu
OffRL
292
109
0
28 Mar 2020
Information Directed Sampling for Linear Partial Monitoring
Information Directed Sampling for Linear Partial Monitoring
Johannes Kirschner
Tor Lattimore
Andreas Krause
56
46
0
25 Feb 2020
Beyond UCB: Optimal and Efficient Contextual Bandits with Regression
  Oracles
Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles
Dylan J. Foster
Alexander Rakhlin
291
207
0
12 Feb 2020
Information-Theoretic Confidence Bounds for Reinforcement Learning
Information-Theoretic Confidence Bounds for Reinforcement Learning
Xiuyuan Lu
Benjamin Van Roy
43
60
0
21 Nov 2019
An Adaptive Empirical Bayesian Method for Sparse Deep Learning
An Adaptive Empirical Bayesian Method for Sparse Deep Learning
Wei Deng
Xiao Zhang
F. Liang
Guang Lin
BDL
105
44
0
23 Oct 2019
Adaptive Exploration in Linear Contextual Bandit
Adaptive Exploration in Linear Contextual Bandit
Botao Hao
Tor Lattimore
Csaba Szepesvári
118
74
0
15 Oct 2019
Doubly-Robust Lasso Bandit
Doubly-Robust Lasso Bandit
Gi-Soo Kim
M. Paik
51
62
0
26 Jul 2019
On the Performance of Thompson Sampling on Logistic Bandits
On the Performance of Thompson Sampling on Logistic Bandits
Shi Dong
Tengyu Ma
Benjamin Van Roy
45
39
0
12 May 2019
First-Order Bayesian Regret Analysis of Thompson Sampling
First-Order Bayesian Regret Analysis of Thompson Sampling
Sébastien Bubeck
Mark Sellke
32
17
0
02 Feb 2019
An Information-Theoretic Approach to Minimax Regret in Partial
  Monitoring
An Information-Theoretic Approach to Minimax Regret in Partial Monitoring
Tor Lattimore
Csaba Szepesvári
35
70
0
01 Feb 2019
An Information-Theoretic Analysis for Thompson Sampling with Many
  Actions
An Information-Theoretic Analysis for Thompson Sampling with Many Actions
Shi Dong
Benjamin Van Roy
38
50
0
30 May 2018
Information Directed Sampling and Bandits with Heteroscedastic Noise
Information Directed Sampling and Bandits with Heteroscedastic Noise
Johannes Kirschner
Andreas Krause
48
122
0
29 Jan 2018
Information Directed Sampling for Stochastic Bandits with Graph Feedback
Information Directed Sampling for Stochastic Bandits with Graph Feedback
Fang Liu
Swapna Buccapatnam
Ness B. Shroff
45
41
0
08 Nov 2017
Minimal Exploration in Structured Stochastic Bandits
Minimal Exploration in Structured Stochastic Bandits
Richard Combes
Stefan Magureanu
Alexandre Proutiere
325
117
0
01 Nov 2017
Ensemble Sampling
Ensemble Sampling
Xiuyuan Lu
Benjamin Van Roy
105
119
0
20 May 2017
The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear
  Bandits
The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits
Tor Lattimore
Csaba Szepesvári
104
105
0
14 Oct 2016
Learning to Optimize via Information-Directed Sampling
Learning to Optimize via Information-Directed Sampling
Daniel Russo
Benjamin Van Roy
138
282
0
21 Mar 2014
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal
Daniel J. Hsu
Satyen Kale
John Langford
Lihong Li
Robert Schapire
OffRL
308
507
0
04 Feb 2014
Confidence Intervals and Hypothesis Testing for High-Dimensional
  Regression
Confidence Intervals and Hypothesis Testing for High-Dimensional Regression
Adel Javanmard
Andrea Montanari
184
767
0
13 Jun 2013
Learning to Optimize Via Posterior Sampling
Learning to Optimize Via Posterior Sampling
Daniel Russo
Benjamin Van Roy
173
699
0
11 Jan 2013
Thompson Sampling for Contextual Bandits with Linear Payoffs
Thompson Sampling for Contextual Bandits with Linear Payoffs
Shipra Agrawal
Navin Goyal
172
997
0
15 Sep 2012
Bandit Theory meets Compressed Sensing for high dimensional Stochastic
  Linear Bandit
Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit
Alexandra Carpentier
Rémi Munos
70
102
0
18 May 2012
Linearly Parameterized Bandits
Linearly Parameterized Bandits
Paat Rusmevichientong
J. Tsitsiklis
306
558
0
18 Dec 2008
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