Peter Bartlett - Google Scholar

Cited by

	All	Since 2015
Citations	35327	15083
h-index	69	53
i10-index	191	131

3500

1750

875

2625

199719981999200020012002200320042005200620072008200920102011201220132014201520162017201820192020103 211 336 394 529 709 850 928 1095 1265 1329 1400 1552 1672 1676 1861 1869 1943 1985 2008 2235 2615 3473 2746

Co-authors

Alex SmolaAmazon Web ServicesVerified email at smola.org
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
Jonathan BaxterVerified email at baxters.biz
Wee Sun LeeProfessor, Department of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
Llew MasonAmazonVerified email at amazon.com
Ambuj Tewari | अम्बुज तिवारीAssociate Professor, Department of Statistics and Department of EECS, University of MichiganVerified email at umich.edu
Dale SchuurmansResearch Scientist, Google Brain / Professor, University of AlbertaVerified email at cs.ualberta.ca
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Alekh AgarwalMicrosoft ResearchVerified email at microsoft.com
Yasin Abbasi-YadkoriDeepMindVerified email at google.com
Benjamin I. P. RubinsteinAssociate Professor, School of Computing and Information Systems, The University of MelbourneVerified email at unimelb.edu.au
Jacob AbernethyAssistant Professor, University of MichiganVerified email at umich.edu
Gabor LugosiICREA and Universitat Pompeu FabraVerified email at upf.edu
Nello CristianiniUniversity of BristolVerified email at bristol.ac.uk
Philip LongGoogleVerified email at google.com
Jon McAuliffeProfessor (Adj.) of Statistics, University of California, BerkeleyVerified email at stat.berkeley.edu
Marcus FreanVictoria University of WellingtonVerified email at ecs.vuw.ac.nz
Yoav FreundUCSDVerified email at eng.ucsd.edu
Gert LanckrietProfessor, UCSDVerified email at eng.ucsd.edu

Peter Bartlett

Professor, EECS and Statistics, UC Berkeley

Verified email at cs.berkeley.edu - Homepage

machine learning statistical learning theory adaptive control


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Boosting the margin: A new explanation for the effectiveness of voting methods RE Schapire, Y Freund, P Bartlett, WS Lee The annals of statistics 26 (5), 1651-1686, 1998	3290	1998
New support vector algorithms B Schölkopf, AJ Smola, RC Williamson, PL Bartlett Neural computation 12 (5), 1207-1245, 2000	3200	2000
Learning the kernel matrix with semidefinite programming GRG Lanckriet, N Cristianini, P Bartlett, LE Ghaoui, MI Jordan Journal of Machine learning research 5 (Jan), 27-72, 2004	2752	2004
Rademacher and Gaussian complexities: Risk bounds and structural results PL Bartlett, S Mendelson Journal of Machine Learning Research 3 (Nov), 463-482, 2002	1758	2002
Neural network learning: Theoretical foundations M Anthony, PL Bartlett cambridge university press, 2009	1659	2009
For valid generalization the size of the weights is more important than the size of the network PL Bartlett Advances in neural information processing systems, 134-140, 1997	1484	1997
Regularization networks and support vector machines T Evgeniou, M Pontil, T Poggio Advances in computational mathematics 13 (1), 1, 2000	1467	2000
Convexity, classification, and risk bounds PL Bartlett, MI Jordan, JD McAuliffe Journal of the American Statistical Association 101 (473), 138-156, 2006	1186	2006
Boosting algorithms as gradient descent L Mason, J Baxter, PL Bartlett, MR Frean Advances in neural information processing systems, 512-518, 2000	889	2000
FaST linear mixed models for genome-wide association studies C Lippert, J Listgarten, Y Liu, CM Kadie, RI Davidson, D Heckerman Nature methods 8 (10), 833-835, 2011	830	2011
Infinite-horizon policy-gradient estimation J Baxter, PL Bartlett Journal of Artificial Intelligence Research 15, 319-350, 2001	810	2001
Structural risk minimization over data-dependent hierarchies J Shawe-Taylor, PL Bartlett, RC Williamson, M Anthony IEEE transactions on Information Theory 44 (5), 1926-1940, 1998	637	1998
Local rademacher complexities PL Bartlett, O Bousquet, S Mendelson The Annals of Statistics 33 (4), 1497-1537, 2005	576	2005
Learning the kernel function via regularization CA Micchelli, M Pontil Journal of machine learning research 6 (Jul), 1099-1125, 2005	441	2005
Generalized support vector machines O Mangasarian	425	1998
Spectrally-normalized margin bounds for neural networks PL Bartlett, DJ Foster, MJ Telgarsky Advances in Neural Information Processing Systems, 6240-6249, 2017	421	2017
Sparse greedy Gaussian process regression AJ Smola, PL Bartlett Advances in neural information processing systems, 619-625, 2001	402	2001
Model selection and error estimation PL Bartlett, S Boucheron, G Lugosi Machine Learning 48 (1-3), 85-113, 2002	388	2002
Advances in large margin classifiers AJ Smola, PJ Bartlett, D Schuurmans, B Schölkopf MIT press, 2000	385	2000
A comment on D PL Bartlett, MI Jordan, JD Mcauliffe V. Lindley’s statistical paradox, Biometrika, 1957	383	1957

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Upload PDF

Follow this author

Cited by

Co-authors