Rocco Anthony Servedio

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Ryan O'DonnellProfessor, Computer Science Department, Carnegie MellonVerified email at cs.cmu.edu
Ilias DiakonikolasUniversity of Wisconsin-MadisonVerified email at wisc.edu
Li-Yang TanStanford UniversityVerified email at cs.stanford.edu
Adam KlivansProfessor of Computer Science, University of Texas at AustinVerified email at cs.utexas.edu
Xi ChenColumbia UniversityVerified email at cs.columbia.edu
Anindya DeUniversity of PennsylvaniaVerified email at seas.upenn.edu
Andrew WanSnapVerified email at cs.columbia.edu
Jon FeldmanResearcher, GoogleVerified email at google.com
Homin K. LeeDatadogVerified email at columbia.edu
Parikshit GopalanAppleVerified email at apple.com
Tal MalkinProfessor of Computer Science, Columbia UniversityVerified email at columbia.edu
Constantinos DaskalakisProfessor of Computer Science, MITVerified email at csail.mit.edu
Jeffrey C. JacksonProfessor of Computer Science, Duquesne UniversityVerified email at duq.edu
Kevin MatulefMIT, Tsinghua, AarhusVerified email at mit.edu
Ronitt RubinfeldProfessor of Computer Science, MIT and Tel Aviv UniversityVerified email at csail.mit.edu
Emanuele ViolaProfessor of Computer Science, Northeastern UniversityVerified email at ccs.neu.edu
Elchanan MosselProfessor of Mathematics, MITVerified email at mit.edu
Shivam NadimpalliMassachusetts Institute of TechnologyVerified email at mit.edu
Roni KhardonProfessor of Computer Science, Indiana University, BloomingtonVerified email at iu.edu
Clément L. CanonneUniversity of SydneyVerified email at sydney.edu.au

Rocco Anthony Servedio

Department of Computer Science, Columbia University

Verified email at columbia.edu - Homepage

Theoretical computer science computational learning theory computational complexity theory machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Random classification noise defeats all convex potential boosters PM Long, RA Servedio Proceedings of the 25th international conference on Machine learning, 608-615, 2008	360	2008
Agnostically learning halfspaces AT Kalai, AR Klivans, Y Mansour, RA Servedio SIAM Journal on Computing 37 (6), 1777-1805, 2008	358	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	294*	2004
Learning DNF in time AR Klivans, R Servedio Proceedings of the thirty-third annual ACM symposium on Theory of computing …, 2001	257	2001
Smooth boosting and learning with malicious noise RA Servedio The Journal of Machine Learning Research 4, 633-648, 2003	245	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	234	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	228	2004
Bounded independence fools halfspaces I Diakonikolas, P Gopalan, R Jaiswal, RA Servedio, E Viola SIAM Journal on Computing 39 (8), 3441-3462, 2010	162	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	162	2005
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
Equivalences and separations between quantum and classical learnability RA Servedio, SJ Gortler SIAM Journal on Computing 33 (5), 1067-1092, 2004	144	2004
Learning monotone decision trees in polynomial time R O'Donnell, RA Servedio SIAM Journal on Computing 37 (3), 827-844, 2007	138	2007
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	132	2008
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	131	2008
Learning Halfspaces with Malicious Noise. AR Klivans, PM Long, RA Servedio Journal of Machine Learning Research 10 (12), 2009	129	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	128	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	122	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	120	2011

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