David Pal - Google Scholar Citations

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	All	Since 2014
Citations	1849	1318
h-index	17	15
i10-index	20	19

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Csaba SzepesvariDeepMind & Department of Computing Science, University of AlbertaVerified email at cs.ualberta.ca
Shai Ben-DavidUniverity of Waterloo, CanadaVerified email at uwaterloo.ca
Tyler LuResearch Scientist, GoogleVerified email at cs.toronto.edu
Martin PálGoogle, Inc.Verified email at google.com
Yasin Abbasi-YadkoriResearcher, VinAIVerified email at vinai.io
Gábor BartókETH ZurichVerified email at ualberta.ca
Francesco OrabonaAssistant Professor, Boston UniversityVerified email at orabona.com
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
S MuthukrishnanRutgers UnivVerified email at cs.rutgers.edu
Ulrike von LuxburgUniversity of TuebingenVerified email at informatik.uni-tuebingen.de
Shai Shalev-ShwartzThe Hebrew UniversityVerified email at cs.huji.ac.il
Gagan AggarwalResearch Scientist, GoogleVerified email at google.com
Hans Ulrich SimonProfessor of Computer Science, Ruhr-University BochumVerified email at rub.de
Satyen KaleStaff Research Scientist, Google ResearchVerified email at google.com
Zohar KarninamazonVerified email at amazon.com
András AntosBudapest University of Technology and EconomicsVerified email at cs.bme.hu
Tengyuan LiangUniversity of Chicago, Booth School of BusinessVerified email at chicagobooth.edu
Balazs Szorenyiresearch fellow at the Research Group on Artificial Intelligence of the Hungarian Academy ofVerified email at inf.u-szeged.hu
Gagan GoelResearch Scientist, GoogleVerified email at google.com
Utkarsh UpadhyayReasonal Inc.Verified email at mpi-sws.org

David Pal

Principal Applied Researcher, Expedia Group

Verified email at expedia.com - Homepage

Machine Learning Algorithms Game Theory Combinatorics Probability Theory


Title	Cited by	Year
Improved algorithms for linear stochastic bandits Y Abbasi-Yadkori, D Pál, C Szepesvári Advances in Neural Information Processing Systems, 2312-2320, 2011	456	2011
A sober look at clustering stability S Ben-David, U Von Luxburg, D Pál International Conference on Computational Learning Theory, 5-19, 2006	238	2006
Contextual multi-armed bandits T Lu, D Pál, M Pál Proceedings of the Thirteenth international conference on Artificial …, 2010	175	2010
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, 1849-1857, 2010	132	2010
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	114	2008
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	110	2009
Impossibility theorems for domain adaptation S Ben-David, T Lu, T Luu, D Pál International Conference on Artificial Intelligence and Statistics, 129-136, 2010	102	2010
Stability of k-means clustering S Ben-David, D Pál, HU Simon International Conference on Computational Learning Theory, 20-34, 2007	83	2007
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	75	2014
Agnostic Online Learning. S Ben-David, D Pál, S Shalev-Shwartz COLT 3, 1, 2009	73	2009
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	63	2012
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	42	2011
Coin betting and parameter-free online learning F Orabona, D Pál Advances in Neural Information Processing Systems, 577-585, 2016	34	2016
Toward a classification of finite partial-monitoring games A Antos, G Bartók, D Pál, C Szepesvári Theoretical Computer Science 473, 77-99, 2013	22	2013
Scale-free algorithms for online linear optimization F Orabona, D Pál International Conference on Algorithmic Learning Theory, 287-301, 2015	19	2015
Toward a classification of finite partial-monitoring games G Bartók, D Pál, C Szepesvári International Conference on Algorithmic Learning Theory, 224-238, 2010	19	2010
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	17	2011
Scale-free online learning F Orabona, D Pál Theoretical Computer Science 716, 50-69, 2018	15	2018
Learning low density separators S Ben-David, T Lu, D Pál, M Sotáková Artificial Intelligence and Statistics, 25-32, 2009	15	2009
Adaptive feature selection: Computationally efficient online sparse linear regression under rip S Kale, Z Karnin, T Liang, D Pál Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017	10	2017

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