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2003.01922
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Taking a hint: How to leverage loss predictors in contextual bandits?
Annual Conference Computational Learning Theory (COLT), 2020
4 March 2020
Chen-Yu Wei
Haipeng Luo
Alekh Agarwal
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Papers citing
"Taking a hint: How to leverage loss predictors in contextual bandits?"
38 / 38 papers shown
Variance-Aware Feel-Good Thompson Sampling for Contextual Bandits
Xuheng Li
Quanquan Gu
153
1
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03 Nov 2025
Efficiently Solving Discounted MDPs with Predictions on Transition Matrices
Lixing Lyu
Jiashuo Jiang
Wang Chi Cheung
345
3
0
24 Feb 2025
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Chenlu Ye
Yujia Jin
Alekh Agarwal
Tong Zhang
491
1
0
04 Feb 2025
How Does Variance Shape the Regret in Contextual Bandits?
Neural Information Processing Systems (NeurIPS), 2024
Zeyu Jia
Jian Qian
Alexander Rakhlin
Chen-Yu Wei
504
10
0
16 Oct 2024
A Parametric Contextual Online Learning Theory of Brokerage
François Bachoc
Tommaso Cesari
Roberto Colomboni
324
2
0
22 May 2024
Online Bandits with (Biased) Offline Data: Adaptive Learning under Distribution Mismatch
International Conference on Machine Learning (ICML), 2024
Wang Chi Cheung
Lixing Lyu
OffRL
481
12
0
04 May 2024
Online Learning in Contextual Second-Price Pay-Per-Click Auctions
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Mengxiao Zhang
Haipeng Luo
322
6
0
08 Oct 2023
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Zhihan Xiong
Romain Camilleri
Maryam Fazel
Lalit P. Jain
Kevin Jamieson
374
2
0
27 Jul 2023
Online Resource Allocation: Bandits feedback and Advice on Time-varying Demands
Lixing Lyu
Wang Chi Cheung
301
0
0
08 Feb 2023
Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions
Neural Information Processing Systems (NeurIPS), 2022
Wei Zhang
Yanjun Han
Zhengyuan Zhou
Aaron Flores
Tsachy Weissman
217
12
0
05 Nov 2022
Improved Adaptive Algorithm for Scalable Active Learning with Weak Labeler
Yifang Chen
Karthik Sankararaman
A. Lazaric
Matteo Pirotta
Dmytro Karamshuk
Qifan Wang
Karishma Mandyam
Sinong Wang
Han Fang
155
3
0
04 Nov 2022
Leveraging Initial Hints for Free in Stochastic Linear Bandits
International Conference on Algorithmic Learning Theory (ALT), 2022
Ashok Cutkosky
Christoph Dann
Abhimanyu Das
Qiuyi
Qiuyi Zhang
184
6
0
08 Mar 2022
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
International Conference on Machine Learning (ICML), 2021
Andrew Wagenmaker
Yifang Chen
Max Simchowitz
S. Du
Kevin Jamieson
359
49
0
07 Dec 2021
Fast Rates for Nonparametric Online Learning: From Realizability to Learning in Games
C. Daskalakis
Noah Golowich
325
28
0
17 Nov 2021
Can Q-Learning be Improved with Advice?
Annual Conference Computational Learning Theory (COLT), 2021
Noah Golowich
Ankur Moitra
OffRL
398
16
0
25 Oct 2021
Corruption Robust Active Learning
Neural Information Processing Systems (NeurIPS), 2021
Yifang Chen
S. Du
Kevin Jamieson
206
5
0
21 Jun 2021
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously
International Conference on Machine Learning (ICML), 2021
Chung-Wei Lee
Haipeng Luo
Chen-Yu Wei
Mengxiao Zhang
Xiaojin Zhang
281
53
0
11 Feb 2021
Multitask Bandit Learning Through Heterogeneous Feedback Aggregation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Zhi Wang
Chicheng Zhang
Manish Singh
L. Riek
Kamalika Chaudhuri
480
26
0
29 Oct 2020
Mean estimation and regression under heavy-tailed distributions--a survey
Foundations of Computational Mathematics (FoCM), 2019
Gabor Lugosi
S. Mendelson
331
284
0
10 Jun 2019
Equipping Experts/Bandits with Long-term Memory
Neural Information Processing Systems (NeurIPS), 2019
Kai Zheng
Haipeng Luo
Ilias Diakonikolas
Liwei Wang
OffRL
207
15
0
30 May 2019
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting
A. Krishnamurthy
John Langford
Aleksandrs Slivkins
Chicheng Zhang
OffRL
475
72
0
05 Feb 2019
A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-free
Yifang Chen
Chung-Wei Lee
Haipeng Luo
Chen-Yu Wei
369
143
0
03 Feb 2019
Improved Path-length Regret Bounds for Bandits
Annual Conference Computational Learning Theory (COLT), 2019
Sébastien Bubeck
Yuanzhi Li
Haipeng Luo
Chen-Yu Wei
362
47
0
29 Jan 2019
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits
Zeyuan Allen-Zhu
Sébastien Bubeck
Yuanzhi Li
LRM
296
33
0
09 Feb 2018
More Adaptive Algorithms for Adversarial Bandits
Chen-Yu Wei
Haipeng Luo
693
201
0
10 Jan 2018
Tracking the Best Expert in Non-stationary Stochastic Environments
Chen-Yu Wei
Yi-Te Hong
Chi-Jen Lu
281
63
0
02 Dec 2017
Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits
Neural Information Processing Systems (NeurIPS), 2016
Vasilis Syrgkanis
Haipeng Luo
A. Krishnamurthy
Robert Schapire
284
43
0
01 Jun 2016
Efficient Algorithms for Adversarial Contextual Learning
Vasilis Syrgkanis
A. Krishnamurthy
Robert Schapire
361
83
0
08 Feb 2016
Fast Convergence of Regularized Learning in Games
Vasilis Syrgkanis
Alekh Agarwal
Haipeng Luo
Robert Schapire
605
301
0
02 Jul 2015
The Computational Power of Optimization in Online Learning
Symposium on the Theory of Computing (STOC), 2015
Elad Hazan
Tomer Koren
563
73
0
08 Apr 2015
Doubly Robust Policy Evaluation and Optimization
Miroslav Dudík
D. Erhan
John Langford
Lihong Li
OffRL
426
311
0
10 Mar 2015
Strongly Adaptive Online Learning
Amit Daniely
Alon Gonen
Shai Shalev-Shwartz
ODL
650
193
0
25 Feb 2015
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
International Conference on Machine Learning (ICML), 2014
Alekh Agarwal
Daniel J. Hsu
Satyen Kale
John Langford
Lihong Li
Robert Schapire
OffRL
995
543
0
04 Feb 2014
Optimization, Learning, and Games with Predictable Sequences
Neural Information Processing Systems (NeurIPS), 2013
Alexander Rakhlin
Karthik Sridharan
538
416
0
08 Nov 2013
Online Learning with Predictable Sequences
Annual Conference Computational Learning Theory (COLT), 2012
Alexander Rakhlin
Karthik Sridharan
572
410
0
18 Aug 2012
Efficient Optimal Learning for Contextual Bandits
Conference on Uncertainty in Artificial Intelligence (UAI), 2011
Miroslav Dudík
Daniel J. Hsu
Satyen Kale
Nikos Karampatziakis
John Langford
L. Reyzin
Tong Zhang
427
320
0
13 Jun 2011
Challenging the empirical mean and empirical variance: a deviation study
O. Catoni
669
505
0
10 Sep 2010
Contextual Bandit Algorithms with Supervised Learning Guarantees
International Conference on Artificial Intelligence and Statistics (AISTATS), 2010
A. Beygelzimer
John Langford
Lihong Li
L. Reyzin
Robert Schapire
OffRL
582
346
0
22 Feb 2010
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