Rocco Anthony Servedio

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Ryan O'DonnellProfessor, Computer Science Department, Carnegie MellonCorreu electrònic verificat a cs.cmu.edu
Ilias DiakonikolasUniversity of Wisconsin-MadisonCorreu electrònic verificat a wisc.edu
Li-Yang TanStanford UniversityCorreu electrònic verificat a cs.stanford.edu
Adam KlivansProfessor of Computer Science, University of Texas at AustinCorreu electrònic verificat a cs.utexas.edu
Xi ChenColumbia UniversityCorreu electrònic verificat a cs.columbia.edu
Anindya DeUniversity of PennsylvaniaCorreu electrònic verificat a seas.upenn.edu
Andrew WanSnapCorreu electrònic verificat a cs.columbia.edu
Jon FeldmanResearcher, GoogleCorreu electrònic verificat a google.com
Homin K. LeeDatadogCorreu electrònic verificat a columbia.edu
Tal MalkinProfessor of Computer Science, Columbia UniversityCorreu electrònic verificat a columbia.edu
Constantinos DaskalakisProfessor of Computer Science, MITCorreu electrònic verificat a csail.mit.edu
Parikshit GopalanAppleCorreu electrònic verificat a apple.com
Emanuele ViolaProfessor of Computer Science, Northeastern UniversityCorreu electrònic verificat a ccs.neu.edu
Jeffrey C. JacksonProfessor of Computer Science, Duquesne UniversityCorreu electrònic verificat a duq.edu
Kevin MatulefMIT, Tsinghua, AarhusCorreu electrònic verificat a mit.edu
Ronitt RubinfeldProfessor of Computer Science, MIT and Tel Aviv UniversityCorreu electrònic verificat a csail.mit.edu
Shivam NadimpalliMassachusetts Institute of TechnologyCorreu electrònic verificat a mit.edu
Elchanan MosselProfessor of Mathematics, MITCorreu electrònic verificat a mit.edu
Roni KhardonProfessor of Computer Science, Indiana University, BloomingtonCorreu electrònic verificat a iu.edu
Clément L. CanonneUniversity of SydneyCorreu electrònic verificat a sydney.edu.au

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Rocco Anthony Servedio

Department of Computer Science, Columbia University

Correu electrònic verificat a columbia.edu - Pàgina d'inici

Theoretical computer science computational learning theory computational complexity theory machine learning


Títol Ordena per cites Ordena per any Ordena per títol	Citada per Citada per	Any
Random classification noise defeats all convex potential boosters PM Long, RA Servedio Proceedings of the 25th international conference on Machine learning, 608-615, 2008	366	2008
Agnostically learning halfspaces AT Kalai, AR Klivans, Y Mansour, RA Servedio SIAM Journal on Computing 37 (6), 1777-1805, 2008	364	2008
Learning functions of k relevant variables E Mossel, R O'Donnell, RA Servedio Journal of Computer and System Sciences 69 (3), 421-434, 2004	298*	2004
Learning DNF in time AR Klivans, R Servedio Proceedings of the thirty-third annual ACM symposium on Theory of computing …, 2001	260	2001
Smooth boosting and learning with malicious noise RA Servedio Journal of Machine Learning Research 4 (Sep), 633-648, 2003	248	2003
On the capacity of secure network coding J Feldman, T Malkin, C Stein, RA Servedio Proc. 42nd Annual Allerton Conference on Communication, Control, and …, 2004	236	2004
Learning intersections and thresholds of halfspaces AR Klivans, R O'Donnell, RA Servedio Journal of Computer and System Sciences 68 (4), 808-840, 2004	233	2004
Bounded independence fools halfspaces I Diakonikolas, P Gopalan, R Jaiswal, RA Servedio, E Viola SIAM Journal on Computing 39 (8), 3441-3462, 2010	164	2010
Every decision tree has an influential variable R O'Donnell, M Saks, O Schramm, RA Servedio 46th annual IEEE symposium on foundations of computer science (FOCS'05), 31-39, 2005	163	2005
Equivalences and separations between quantum and classical learnability RA Servedio, SJ Gortler SIAM Journal on Computing 33 (5), 1067-1092, 2004	145	2004
Learning poisson binomial distributions C Daskalakis, I Diakonikolas, RA Servedio Proceedings of the forty-fourth annual ACM symposium on Theory of computing …, 2012	144	2012
Learning monotone decision trees in polynomial time R O'Donnell, RA Servedio SIAM Journal on Computing 37 (3), 827-844, 2007	138	2007
Learning geometric concepts via Gaussian surface area AR Klivans, R O'Donnell, RA Servedio 2008 49th Annual IEEE Symposium on Foundations of Computer Science, 541-550, 2008	137	2008
Efficient density estimation via piecewise polynomial approximation SO Chan, I Diakonikolas, RA Servedio, X Sun Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014	135	2014
Learning mixtures of product distributions over discrete domains J Feldman, R O'Donnell, RA Servedio SIAM Journal on Computing 37 (5), 1536-1564, 2008	133	2008
Learning Halfspaces with Malicious Noise. AR Klivans, PM Long, RA Servedio Journal of Machine Learning Research 10 (12), 2009	130	2009
LP decoding corrects a constant fraction of errors J Feldman, T Malkin, RA Servedio, C Stein, MJ Wainwright IEEE Transactions on Information Theory 53 (1), 82-89, 2006	130	2006
Testing halfspaces K Matulef, R O'Donnell, R Rubinfeld, RA Servedio SIAM Journal on Computing 39 (5), 2004-2047, 2010	123	2010
Testing for concise representations I Diakonikolas, HK Lee, K Matulef, K Onak, R Rubinfeld, RA Servedio, ... 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07), 549-558, 2007	123	2007
Testing Fourier dimensionality and sparsity P Gopalan, R O'Donnell, RA Servedio, A Shpilka, K Wimmer SIAM Journal on Computing 40 (4), 1075-1100, 2011	121	2011

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