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 YadkoriDeepMindVerified email at google.com
Tyler LuResearch Scientist, GoogleVerified email at cs.toronto.edu
Martin PálGoogle, Inc.Verified email at google.com
Francesco OrabonaAssociate Professor, Boston UniversityVerified email at orabona.com
Gábor BartókETH ZurichVerified email at ualberta.ca
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Shai Shalev-ShwartzThe Hebrew UniversityVerified email at cs.huji.ac.il
S MuthukrishnanRutgers UnivVerified email at cs.rutgers.edu
Ulrike von LuxburgUniversity of TübingenVerified email at informatik.uni-tuebingen.de
Satyen KaleStaff Research Scientist, Google ResearchVerified email at google.com
Gagan AggarwalResearch Scientist, GoogleVerified email at google.com
Alexander RakhlinProfessor, MITVerified email at mit.edu
Balazs SzorenyiSr Research Scientist at Yahoo ResearchVerified email at yahooinc.com
Hans Ulrich SimonRetired Professor, Dept. of Math., Ruhr-University BochumVerified email at rub.de
András AntosBudapest University of Technology and EconomicsVerified email at cs.bme.hu
Zohar KarninamazonVerified email at amazon.com
Tengyuan LiangProfessor of Econometrics and Statistics, 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	1379	2011
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	300	2006
Contextual multi-armed bandits T Lu, D Pál, M Pál Proceedings of the Thirteenth international conference on Artificial …, 2010	275	2010
Impossibility theorems for domain adaptation SB David, T Lu, T Luu, D Pál Proceedings of the Thirteenth International Conference on Artificial …, 2010	254	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 23, 2010	176	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	155	2012
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	143	2008
Agnostic Online Learning. S Ben-David, D Pál, S Shalev-Shwartz COLT 3, 1, 2009	136	2009
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	133	2009
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	117	2014
Stability of k-Means Clustering S Ben-David, D Pál, HU Simon Learning Theory: 20th Annual Conference on Learning Theory, COLT 2007, San …, 2007	110	2007
Coin betting and parameter-free online learning F Orabona, D Pál Advances in Neural Information Processing Systems 29, 2016	106	2016
Scale-free online learning F Orabona, D Pál Theoretical Computer Science 716, 50-69, 2018	72	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	52	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	49	2011
Toward a classification of finite partial-monitoring games A Antos, G Bartók, D Pál, C Szepesvári Theoretical Computer Science 473, 77-99, 2013	46	2013
Scale-free algorithms for online linear optimization F Orabona, D Pál Algorithmic Learning Theory: 26th International Conference, ALT 2015, Banff …, 2015	37	2015
Learning low density separators S Ben-David, T Lu, D Pál, M Sotáková Artificial Intelligence and Statistics, 25-32, 2009	20	2009
Optimal non-asymptotic lower bound on the minimax regret of learning with expert advice F Orabona, D Pál arXiv preprint arXiv:1511.02176, 2015	19	2015
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	17	2017

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