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Learning the Linear Quadratic Regulator from Nonlinear Observations

Oct 08, 2020
Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford

* To appear at NeurIPS 2020 

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Better Parameter-free Stochastic Optimization with ODE Updates for Coin-Betting

Jun 12, 2020
Keyi Chen, John Langford, Francesco Orabona


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Efficient Contextual Bandits with Continuous Actions

Jun 10, 2020
Maryam Majzoubi, Chicheng Zhang, Rajan Chari, Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins


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Federated Residual Learning

Mar 28, 2020
Alekh Agarwal, John Langford, Chen-Yu Wei


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Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning

Nov 13, 2019
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford


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Empirical Likelihood for Contextual Bandits

Jun 21, 2019
Nikos Karampatziakis, John Langford, Paul Mineiro


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Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Jun 09, 2019
Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, Alekh Agarwal


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Efficient Forward Architecture Search

May 31, 2019
Hanzhang Hu, John Langford, Rich Caruana, Saurajit Mukherjee, Eric Horvitz, Debadeepta Dey

* preprint 

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Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting

Feb 05, 2019
Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins, Chicheng Zhang


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Provably efficient RL with Rich Observations via Latent State Decoding

Jan 25, 2019
Simon S. Du, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal, Miroslav Dudík, John Langford


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Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback

Jan 02, 2019
Chicheng Zhang, Alekh Agarwal, Hal Daumé III, John Langford, Sahand N Negahban

* 43 pages, 21 figures 

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Model-Based Reinforcement Learning in Contextual Decision Processes

Nov 21, 2018
Wen Sun, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford

* 30 

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On Oracle-Efficient PAC RL with Rich Observations

Oct 31, 2018
Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire

* appearing at NIPS 18; full paper including appendix 

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Contextual Memory Trees

Jul 17, 2018
Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro


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A Reductions Approach to Fair Classification

Jul 16, 2018
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna Wallach


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Learning Deep ResNet Blocks Sequentially using Boosting Theory

Jun 14, 2018
Furong Huang, Jordan Ash, John Langford, Robert Schapire

* Accepted to ICML 2018 

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Efficient Contextual Bandits in Non-stationary Worlds

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


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A Contextual Bandit Bake-off

May 30, 2018
Alberto Bietti, Alekh Agarwal, John Langford


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Active Learning for Cost-Sensitive Classification

Nov 13, 2017
Akshay Krishnamurthy, Alekh Agarwal, Tzu-Kuo Huang, Hal Daume III, John Langford


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Off-policy evaluation for slate recommendation

Nov 06, 2017
Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík, John Langford, Damien Jose, Imed Zitouni

* 31 pages (9 main paper, 20 supplementary), 12 figures (2 main paper, 10 supplementary) 

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Efficient Second Order Online Learning by Sketching

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


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Mapping Instructions and Visual Observations to Actions with Reinforcement Learning

Jul 22, 2017
Dipendra Misra, John Langford, Yoav Artzi

* In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017 

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Making Contextual Decisions with Low Technical Debt

May 09, 2017
Alekh Agarwal, Sarah Bird, Markus Cozowicz, Luong Hoang, John Langford, Stephen Lee, Jiaji Li, Dan Melamed, Gal Oshri, Oswaldo Ribas, Siddhartha Sen, Alex Slivkins


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Contextual Decision Processes with Low Bellman Rank are PAC-Learnable

Dec 01, 2016
Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire

* 42 pages, 1 figure 

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Logarithmic Time One-Against-Some

Dec 01, 2016
Hal Daume III, Nikos Karampatziakis, John Langford, Paul Mineiro


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PAC Reinforcement Learning with Rich Observations

Oct 28, 2016
Akshay Krishnamurthy, Alekh Agarwal, John Langford


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Search Improves Label for Active Learning

Oct 24, 2016
Alina Beygelzimer, Daniel Hsu, John Langford, Chicheng Zhang

* 32 pages; NIPS 2016 

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A Credit Assignment Compiler for Joint Prediction

Jun 01, 2016
Kai-Wei Chang, He He, Hal Daumé III, John Langford, Stephane Ross


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The Offset Tree for Learning with Partial Labels

Apr 03, 2016
Alina Beygelzimer, John Langford


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