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Mutual Information Constraints for Monte-Carlo Objectives

Dec 01, 2020
Gábor Melis, András György, Phil Blunsom

* 32 pages, 29 figures 

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Adapting to Delays and Data in Adversarial Multi-Armed Bandits

Oct 12, 2020
András György, Pooria Joulani


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Mirror Descent and the Information Ratio

Sep 25, 2020
Tor Lattimore, András György


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Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting

Jun 18, 2020
Ilja Kuzborskij, Claire Vernade, András György, Csaba Szepesvári


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Meta-learning of Sequential Strategies

May 08, 2019
Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alex Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin Miller, Mohammad Azar, Ian Osband, Neil Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew Botvinick, Shane Legg

* DeepMind Technical Report (15 pages, 6 figures) 

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Degenerate Feedback Loops in Recommender Systems

Mar 27, 2019
Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli

* Proceedings of AAAI/ACM Conference on AI, Ethics, and Society, Honolulu, HI, USA, January 27-28, 2019 (AIES '19) 

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Detecting Overfitting via Adversarial Examples

Mar 06, 2019
Roman Werpachowski, András György, Csaba Szepesvári

* 25 pages 

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LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration

Jul 02, 2018
Gellért Weisz, András György, Csaba Szepesvári

* to appear at ICML 2018 

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Adaptive MCMC via Combining Local Samplers

Jun 11, 2018
Kiarash Shaloudegi, András György


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A Reinforcement Learning Approach to Age of Information in Multi-User Networks

Jun 01, 2018
Elif Tuğçe Ceran, Deniz Gündüz, András György


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A Modular Analysis of Adaptive (Non-)Convex Optimization: Optimism, Composite Objectives, and Variational Bounds

Sep 08, 2017
Pooria Joulani, András György, Csaba Szepesvári

* Accepted to The 28th International Conference on Algorithmic Learning Theory (ALT 2017). 40 pages 

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SDP Relaxation with Randomized Rounding for Energy Disaggregation

Oct 29, 2016
Kiarash Shaloudegi, András György, Csaba Szepesvári, Wilsun Xu


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(Bandit) Convex Optimization with Biased Noisy Gradient Oracles

Sep 22, 2016
Xiaowei Hu, Prashanth L. A., András György, Csaba Szepesvári


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Chaining Bounds for Empirical Risk Minimization

Sep 07, 2016
Gábor Balázs, András György, Csaba Szepesvári


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Online Learning with Gaussian Payoffs and Side Observations

Oct 27, 2015
Yifan Wu, András György, Csaba Szepesvári


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Fast Cross-Validation for Incremental Learning

Jun 30, 2015
Pooria Joulani, András György, Csaba Szepesvári

* Appearing in the International Joint Conference on Artificial Intelligence (IJCAI-2015), Buenos Aires, Argentina, July 2015 

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Adaptive Monte Carlo via Bandit Allocation

May 13, 2014
James Neufeld, András György, Dale Schuurmans, Csaba Szepesvári

* The 31st International Conference on Machine Learning (ICML 2014) 

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Efficient Multi-Start Strategies for Local Search Algorithms

Jan 16, 2014
András György, Levente Kocsis

* Journal Of Artificial Intelligence Research, Volume 41, pages 407-444, 2011 

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Online Learning under Delayed Feedback

Jun 05, 2013
Pooria Joulani, András György, Csaba Szepesvári

* Extended version of a paper accepted to ICML-2013 

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A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning

Jan 07, 2013
Arash Afkanpour, András György, Csaba Szepesvári, Michael Bowling


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Partition Tree Weighting

Nov 21, 2012
Joel Veness, Martha White, Michael Bowling, András György


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