ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1504.06952
  4. Cited By
Random Forest for the Contextual Bandit Problem - extended version
v1v2v3v4v5v6v7v8v9v10v11v12v13v14v15v16v17v18v19v20v21 (latest)

Random Forest for the Contextual Bandit Problem - extended version

27 April 2015
Raphael Feraud
Robin Allesiardo
Tanguy Urvoy
Fabrice Clérot
ArXiv (abs)PDFHTML

Papers citing "Random Forest for the Contextual Bandit Problem - extended version"

18 / 18 papers shown
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits
Variance-Aware Linear UCB with Deep Representation for Neural Contextual BanditsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
H. Bui
Enrique Mallada
Anqi Liu
1.2K
4
0
08 Nov 2024
LLMs-augmented Contextual Bandit
LLMs-augmented Contextual Bandit
Ali Baheri
Cecilia Ovesdotter Alm
OffRL
288
7
0
03 Nov 2023
Doubly High-Dimensional Contextual Bandits: An Interpretable Model for
  Joint Assortment-Pricing
Doubly High-Dimensional Contextual Bandits: An Interpretable Model for Joint Assortment-PricingSocial Science Research Network (SSRN), 2023
Junhui Cai
Ran Chen
Martin J. Wainwright
Linda H. Zhao
278
7
0
14 Sep 2023
Efficient Online Decision Tree Learning with Active Feature Acquisition
Efficient Online Decision Tree Learning with Active Feature AcquisitionInternational Joint Conference on Artificial Intelligence (IJCAI), 2023
Arman Rahbar
Ziyu Ye
Yuxin Chen
M. Chehreghani
368
2
0
03 May 2023
Universality of parametric Coupling Flows over parametric
  diffeomorphisms
Universality of parametric Coupling Flows over parametric diffeomorphisms
Junlong Lyu
Zhitang Chen
Chang Feng
Wenjing Cun
Shengyu Zhu
Yanhui Geng
Zhijie Xu
Yuxiao Chen
330
3
0
07 Feb 2022
Tsetlin Machine for Solving Contextual Bandit Problems
Tsetlin Machine for Solving Contextual Bandit ProblemsNeural Information Processing Systems (NeurIPS), 2022
Raihan Seraj
Jivitesh Sharma
Ole-Christoffer Granmo
215
16
0
04 Feb 2022
Learning Accurate Decision Trees with Bandit Feedback via Quantized
  Gradient Descent
Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent
Ajaykrishna Karthikeyan
Naman Jain
Nagarajan Natarajan
Prateek Jain
MQ
244
14
0
15 Feb 2021
The Adaptive Doubly Robust Estimator for Policy Evaluation in Adaptive
  Experiments and a Paradox Concerning Logging Policy
The Adaptive Doubly Robust Estimator for Policy Evaluation in Adaptive Experiments and a Paradox Concerning Logging Policy
Masahiro Kato
Shota Yasui
K. McAlinn
OffRL
319
0
0
08 Oct 2020
Stochastic Optimization Forests
Stochastic Optimization Forests
Nathan Kallus
Xiaojie Mao
456
62
0
17 Aug 2020
Combining Offline Causal Inference and Online Bandit Learning for Data
  Driven Decision
Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decision
Li Ye
Yishi Lin
Hong Xie
John C. S. Lui
CML
253
12
0
16 Jan 2020
Exploiting Relevance for Online Decision-Making in High-Dimensions
Exploiting Relevance for Online Decision-Making in High-DimensionsIEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2019
E. Turğay
Cem Bulucu
Cem Tekin
209
4
0
01 Jul 2019
Meta-Learning for Contextual Bandit Exploration
Meta-Learning for Contextual Bandit Exploration
Amr Sharaf
Hal Daumé
OffRL
167
15
0
23 Jan 2019
Decentralized Exploration in Multi-Armed Bandits -- Extended version
Decentralized Exploration in Multi-Armed Bandits -- Extended versionInternational Conference on Machine Learning (ICML), 2018
Raphael Feraud
Réda Alami
Romain Laroche
FedML
426
25
0
19 Nov 2018
Nonparametric Pricing Analytics with Customer Covariates
Nonparametric Pricing Analytics with Customer Covariates
Yi Xiong
G. Gallego
444
54
0
03 May 2018
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep
  Networks for Thompson Sampling
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson SamplingInternational Conference on Learning Representations (ICLR), 2018
C. Riquelme
George Tucker
Jasper Snoek
BDL
356
385
0
26 Feb 2018
Estimation Considerations in Contextual Bandits
Estimation Considerations in Contextual Bandits
Maria Dimakopoulou
Zhengyuan Zhou
Susan Athey
Guido Imbens
519
74
0
19 Nov 2017
Random Shuffling and Resets for the Non-stationary Stochastic Bandit
  Problem
Random Shuffling and Resets for the Non-stationary Stochastic Bandit Problem
Robin Allesiardo
Raphael Feraud
Odalric-Ambrym Maillard
95
1
0
07 Sep 2016
Network of Bandits insure Privacy of end-users
Network of Bandits insure Privacy of end-users
Raphael Féraud
371
1
0
11 Feb 2016
1
Page 1 of 1