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Greedy Algorithm almost Dominates in Smoothed Contextual Bandits
v1v2 (latest)

Greedy Algorithm almost Dominates in Smoothed Contextual Bandits

19 May 2020
Manish Raghavan
Aleksandrs Slivkins
Jennifer Wortman Vaughan
Zhiwei Steven Wu
ArXiv (abs)PDFHTML

Papers citing "Greedy Algorithm almost Dominates in Smoothed Contextual Bandits"

15 / 15 papers shown
Title
Greedy Algorithm for Structured Bandits: A Sharp Characterization of Asymptotic Success / Failure
Greedy Algorithm for Structured Bandits: A Sharp Characterization of Asymptotic Success / Failure
Aleksandrs Slivkins
Yunzong Xu
Shiliang Zuo
539
1
0
06 Mar 2025
Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contexts
Zhuohua Li
Maoli Liu
Xiangxiang Dai
John C. S. Lui
75
2
0
03 Jan 2025
Exploration and Persuasion
Exploration and Persuasion
Aleksandrs Slivkins
420
12
0
22 Oct 2024
Incentivized Exploration via Filtered Posterior Sampling
Incentivized Exploration via Filtered Posterior Sampling
Anand Kalvit
Aleksandrs Slivkins
Yonatan Gur
54
2
0
20 Feb 2024
Thompson Sampling in Partially Observable Contextual Bandits
Thompson Sampling in Partially Observable Contextual Bandits
Hongju Park
Mohamad Kazem Shirani Faradonbeh
67
3
0
15 Feb 2024
Strategic Apple Tasting
Strategic Apple Tasting
Keegan Harris
Chara Podimata
Zhiwei Steven Wu
84
7
0
09 Jun 2023
Repeated Bilateral Trade Against a Smoothed Adversary
Repeated Bilateral Trade Against a Smoothed Adversary
Nicolò Cesa-Bianchi
Tommaso Cesari
Roberto Colomboni
Federico Fusco
S. Leonardi
91
17
0
21 Feb 2023
Bandit Social Learning: Exploration under Myopic Behavior
Bandit Social Learning: Exploration under Myopic Behavior
Kiarash Banihashem
Mohammadtaghi Hajiaghayi
Suho Shin
Aleksandrs Slivkins
430
4
0
15 Feb 2023
Incentive-Aware Recommender Systems in Two-Sided Markets
Incentive-Aware Recommender Systems in Two-Sided Markets
Xiaowu Dai
Wenlu Xu
Yuan Qi
Michael I. Jordan
50
6
0
23 Nov 2022
Efficient Algorithms for Learning to Control Bandits with Unobserved
  Contexts
Efficient Algorithms for Learning to Control Bandits with Unobserved Contexts
Hongju Park
Mohamad Kazem Shirani Faradonbeh
43
6
0
02 Feb 2022
Analysis of Thompson Sampling for Partially Observable Contextual
  Multi-Armed Bandits
Analysis of Thompson Sampling for Partially Observable Contextual Multi-Armed Bandits
Yash J. Patel
Mohamad Kazem Shirani Faradonbeh
62
15
0
23 Oct 2021
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored
  Online Binary Classification
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification
James A. Grant
David S. Leslie
82
3
0
29 Sep 2021
Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment
Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment
Eli Ben-Michael
D. J. Greiner
Kosuke Imai
Zhichao Jiang
OffRL
229
22
0
22 Sep 2021
Exploration and Incentives in Reinforcement Learning
Exploration and Incentives in Reinforcement Learning
Max Simchowitz
Aleksandrs Slivkins
93
18
0
28 Feb 2021
Be Greedy in Multi-Armed Bandits
Be Greedy in Multi-Armed Bandits
Matthieu Jedor
Jonathan Louëdec
Vianney Perchet
397
8
0
04 Jan 2021
1