Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation

Jul 23, 2020
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Rahul Jain


  Access Paper or Ask Questions

Comparator-adaptive Convex Bandits

Jul 16, 2020
Dirk van der Hoeven, Ashok Cutkosky, Haipeng Luo

* 15 pages 

  Access Paper or Ask Questions

Active Online Domain Adaptation

Jun 25, 2020
Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang


  Access Paper or Ask Questions

Open Problem: Model Selection for Contextual Bandits

Jun 19, 2020
Dylan J. Foster, Akshay Krishnamurthy, Haipeng Luo

* COLT 2020 open problem 

  Access Paper or Ask Questions

Linear Last-iterate Convergence for Matrix Games and Stochastic Games

Jun 16, 2020
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang


  Access Paper or Ask Questions

Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs

Jun 14, 2020
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang


  Access Paper or Ask Questions

Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition

Jun 10, 2020
Tiancheng Jin, Haipeng Luo


  Access Paper or Ask Questions

A Model-free Learning Algorithm for Infinite-horizon Average-reward MDPs with Near-optimal Regret

Jun 08, 2020
Mehdi Jafarnia-Jahromi, Chen-Yu Wei, Rahul Jain, Haipeng Luo


  Access Paper or Ask Questions

Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds

Mar 07, 2020
Ehsan Emamjomeh-Zadeh, Chen-Yu Wei, Haipeng Luo, David Kempe


  Access Paper or Ask Questions

Taking a hint: How to leverage loss predictors in contextual bandits?

Mar 04, 2020
Chen-Yu Wei, Haipeng Luo, Alekh Agarwal


  Access Paper or Ask Questions

A Closer Look at Small-loss Bounds for Bandits with Graph Feedback

Feb 02, 2020
Chung-Wei Lee, Haipeng Luo, Mengxiao Zhang


  Access Paper or Ask Questions

Learning Adversarial MDPs with Bandit Feedback and Unknown Transition

Jan 07, 2020
Chi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu

* Improved the algorithm with a tighter confidence set 

  Access Paper or Ask Questions

Fair Contextual Multi-Armed Bandits: Theory and Experiments

Dec 13, 2019
Yifang Chen, Alex Cuellar, Haipeng Luo, Jignesh Modi, Heramb Nemlekar, Stefanos Nikolaidis

* 9 pages, 9 figures 

  Access Paper or Ask Questions

Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes

Oct 15, 2019
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Hiteshi Sharma, Rahul Jain


  Access Paper or Ask Questions

Model selection for contextual bandits

Jun 03, 2019
Dylan J. Foster, Akshay Krishnamurthy, Haipeng Luo


  Access Paper or Ask Questions

Equipping Experts/Bandits with Long-term Memory

May 30, 2019
Kai Zheng, Haipeng Luo, Ilias Diakonikolas, Liwei Wang

* 24 pages 

  Access Paper or Ask Questions

Hypothesis Set Stability and Generalization

Apr 17, 2019
Dylan J. Foster, Spencer Greenberg, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan


  Access Paper or Ask Questions

A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-free

Feb 05, 2019
Yifang Chen, Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei


  Access Paper or Ask Questions

Improved Path-length Regret Bounds for Bandits

Jan 29, 2019
Sébastien Bubeck, Yuanzhi Li, Haipeng Luo, Chen-Yu Wei


  Access Paper or Ask Questions

Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously

Jan 25, 2019
Julian Zimmert, Haipeng Luo, Chen-Yu Wei


  Access Paper or Ask Questions

Efficient Contextual Bandits in Non-stationary Worlds

Jun 07, 2018
Haipeng Luo, Chen-Yu Wei, Alekh Agarwal, John Langford


  Access Paper or Ask Questions

More Adaptive Algorithms for Adversarial Bandits

Jun 07, 2018
Chen-Yu Wei, Haipeng Luo


  Access Paper or Ask Questions

Efficient Online Portfolio with Logarithmic Regret

May 18, 2018
Haipeng Luo, Chen-Yu Wei, Kai Zheng


  Access Paper or Ask Questions

Logistic Regression: The Importance of Being Improper

Mar 25, 2018
Dylan J. Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan


  Access Paper or Ask Questions

Practical Contextual Bandits with Regression Oracles

Mar 03, 2018
Dylan J. Foster, Alekh Agarwal, Miroslav Dudík, Haipeng Luo, Robert E. Schapire


  Access Paper or Ask Questions

Efficient Second Order Online Learning by Sketching

Oct 17, 2017
Haipeng Luo, Alekh Agarwal, Nicolo Cesa-Bianchi, John Langford


  Access Paper or Ask Questions

Variance-Reduced and Projection-Free Stochastic Optimization

Sep 14, 2017
Elad Hazan, Haipeng Luo


  Access Paper or Ask Questions

Corralling a Band of Bandit Algorithms

Jun 06, 2017
Alekh Agarwal, Haipeng Luo, Behnam Neyshabur, Robert E. Schapire

* Accepted to COLT 2017 

  Access Paper or Ask Questions