Dávid Pál

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Csaba SzepesvariDeepMind & University of AlbertaVerified email at cs.ualberta.ca
Shai Ben-DavidUniverity of Waterloo, CanadaVerified email at uwaterloo.ca
Yasin Abbasi YadkoriGoogle DeepMindVerified email at google.com
Tyler LuResearch Scientist, MetaVerified email at cs.toronto.edu
Martin PálGoogle, Inc.Verified email at google.com
Francesco OrabonaAssociate Professor, KAUSTVerified email at orabona.com
Gábor BartókETH ZurichVerified email at ualberta.ca
Shai Shalev-ShwartzThe Hebrew UniversityVerified email at cs.huji.ac.il
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Ulrike von LuxburgUniversity of TübingenVerified email at informatik.uni-tuebingen.de
S MuthukrishnanRutgers UnivVerified email at cs.rutgers.edu
Satyen KaleResearch Scientist, Google ResearchVerified email at google.com
Balazs SzorenyiSr Research Scientist at Yahoo ResearchVerified email at yahooinc.com
Alexander RakhlinProfessor, MITVerified email at mit.edu
Gagan AggarwalResearch Scientist, GoogleVerified email at google.com
Hans Ulrich SimonRetired Professor, Dept. of Math., Ruhr-University BochumVerified email at rub.de
Zohar KarninamazonVerified email at amazon.com
András AntosBudapest University of Technology and EconomicsVerified email at cs.bme.hu
Tengyuan LiangProfessor, University of ChicagoVerified email at chicagobooth.edu
Chansoo LeeGoogleVerified email at google.com

Dávid Pál

Staff Machine Learning Engineer, Instacart

Verified email at instacart.com - Homepage

Machine Learning Algorithms Game Theory Combinatorics Probability Theory


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Improved algorithms for linear stochastic bandits Y Abbasi-Yadkori, D Pál, C Szepesvári Advances in neural information processing systems 24, 2011	2037	2011
Impossibility theorems for domain adaptation SB David, T Lu, T Luu, D Pál Proceedings of the Thirteenth International Conference on Artificial …, 2010	358	2010
Contextual multi-armed bandits T Lu, D Pál, M Pál Proceedings of the Thirteenth international conference on Artificial …, 2010	348	2010
A sober look at clustering stability S Ben-David, U Von Luxburg, D Pál Learning Theory: 19th Annual Conference on Learning Theory, COLT 2006 …, 2006	324	2006
Agnostic Online Learning. S Ben-David, D Pál, S Shalev-Shwartz COLT 3, 1, 2009	197	2009
Estimation of Rényi entropy and mutual information based on generalized nearest-neighbor graphs D Pál, B Póczos, C Szepesvári Advances in neural information processing systems 23, 2010	193	2010
Online-to-confidence-set conversions and application to sparse stochastic bandits Y Abbasi-Yadkori, D Pal, C Szepesvari Artificial Intelligence and Statistics, 1-9, 2012	191	2012
Coin betting and parameter-free online learning F Orabona, D Pál Advances in Neural Information Processing Systems 29, 2016	168	2016
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning. S Ben-David, T Lu, D Pál COLT, 33-44, 2008	165	2008
Partial monitoring—classification, regret bounds, and algorithms G Bartók, DP Foster, D Pál, A Rakhlin, C Szepesvári Mathematics of Operations Research 39 (4), 967-997, 2014	144	2014
General auction mechanism for search advertising G Aggarwal, S Muthukrishnan, D Pál, M Pál Proceedings of the 18th international conference on World wide web, 241-250, 2009	135	2009
Stability of k-Means Clustering S Ben-David, D Pál, HU Simon Learning Theory: 20th Annual Conference on Learning Theory, COLT 2007, San …, 2007	127	2007
Scale-free online learning F Orabona, D Pál Theoretical Computer Science 716, 50-69, 2018	111	2018
Online least squares estimation with self-normalized processes: An application to bandit problems Y Abbasi-Yadkori, D Pál, C Szepesvári arXiv preprint arXiv:1102.2670, 2011	77	2011
Minimax regret of finite partial-monitoring games in stochastic environments G Bartók, D Pál, C Szepesvári Proceedings of the 24th Annual Conference on Learning Theory, 133-154, 2011	58	2011
Scale-free algorithms for online linear optimization F Orabona, D Pál International Conference on Algorithmic Learning Theory, 287-301, 2015	55	2015
Toward a classification of finite partial-monitoring games A Antos, G Bartók, D Pál, C Szepesvári Theoretical Computer Science 473, 77-99, 2013	51	2013
Adaptive feature selection: Computationally efficient online sparse linear regression under rip S Kale, Z Karnin, T Liang, D Pál International Conference on Machine Learning, 1780-1788, 2017	24	2017
Optimal non-asymptotic lower bound on the minimax regret of learning with expert advice F Orabona, D Pál arXiv preprint arXiv:1511.02176, 2015	23	2015
Learning low density separators S Ben-David, T Lu, D Pál, M Sotáková Artificial Intelligence and Statistics, 25-32, 2009	23	2009

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