Massimiliano Pontil

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TOMASO POGGIOMcDermott Professor in Brain Sciences, MITVerified email at ai.mit.edu
Andreas ArgyriouMicrosoft UKVerified email at alum.mit.edu
Paolo FrasconiProfessor of Computer Science, Università di FirenzeVerified email at dsi.unifi.it
Michele DoniniAmazonVerified email at amazon.com
alessandro verriprofessor of computer science, dibris, università degli studi di genovaVerified email at unige.it
Bernardino Romera-ParedesGoogle DeepMindVerified email at google.com
Carlo CilibertoUniversity College LondonVerified email at ucl.ac.uk
Luca FranceschiUniversity College LondonVerified email at iit.it
Mark HerbsterUniversity College LondonVerified email at cs.ucl.ac.uk
Luca BaldassarreLead Data Scientist, Swiss ReVerified email at swissre.com
Andre ElisseeffGoogleVerified email at google.com
Luca OnetoDIBRIS - University of GenoaVerified email at unige.it
Sayan MukherjeeDuke University, MITVerified email at stat.duke.edu
arthur grettonGatsby Computational Neuroscience Unit, UCLVerified email at gatsby.ucl.ac.uk
Yiming YingProfessor, Department of Mathematics and Statistics, University at Albany, SUNYVerified email at albany.edu
Cecilia MascoloUniversity of CambridgeVerified email at cl.cam.ac.uk
Anastasios NoulasNew York University, Center for Data Science, Moore-Sloan FellowVerified email at cl.cam.ac.uk
Saverio SalzoResearcher, Istituto Italiano di Tecnologia, GenovaVerified email at iit.it
Bernd HeiseleVerified email at mty.ai
Salvatore ScellatoDeepMind, Google, University of CambridgeVerified email at cl.cam.ac.uk

Massimiliano Pontil

Istituto Italiano di Tecnologia & University College London

Verified email at iit.it - Homepage

Applied Mathematics Learning Theory Machine Learning Statistics


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Regularized multi--task learning T Evgeniou, M Pontil Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004	1691	2004
Multi-task feature learning A Argyriou, T Evgeniou, M Pontil Advances in neural information processing systems 19, 41, 2007	1600*	2007
Convex multi-task feature learning A Argyriou, T Evgeniou, M Pontil Machine learning 73 (3), 243-272, 2008	1578	2008
Regularization networks and support vector machines T Evgeniou, M Pontil, T Poggio Advances in computational mathematics 13 (1), 1-50, 2000	1543	2000
Feature selection for SVMs J Weston, S Mukherjee, O Chapelle, M Pontil, T Poggio, V Vapnik NIPS 12, 668-674, 2000	1441	2000
Support vector machines for 3D object recognition M Pontil, A Verri IEEE transactions on pattern analysis and machine intelligence 20 (6), 637-646, 1998	1184	1998
Learning multiple tasks with kernel methods. T Evgeniou, CA Micchelli, M Pontil Journal of machine learning research 6 (4), 2005	1025	2005
PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments DT Jones, DWA Buchan, D Cozzetto, M Pontil Bioinformatics 28 (2), 184-190, 2012	742	2012
A tale of many cities: universal patterns in human urban mobility A Noulas, S Scellato, R Lambiotte, M Pontil, C Mascolo PloS one 7 (5), e37027, 2012	702	2012
An empirical study of geographic user activity patterns in foursquare A Noulas, S Scellato, C Mascolo, M Pontil Proceedings of the International AAAI Conference on Web and Social Media 5 (1), 2011	664	2011
On learning vector-valued functions CA Micchelli, M Pontil Neural computation 17 (1), 177-204, 2005	546	2005
Predicting structured data G BakIr, T Hofmann, B Schölkopf, AJ Smola, B Taskar MIT press, 2007	493	2007
Learning the Kernel Function via Regularization. CA Micchelli, M Pontil Journal of machine learning research 6 (7), 2005	490	2005
Optimal kernel choice for large-scale two-sample tests A Gretton, D Sejdinovic, H Strathmann, S Balakrishnan, M Pontil, ... Advances in neural information processing systems, 1205-1213, 2012	441	2012
Advances in large margin classifiers AJ Smola, PJ Bartlett, D Schuurmans, B Schölkopf MIT press, 2000	402	2000
Empirical Bernstein bounds and sample variance penalization A Maurer, M Pontil arXiv preprint arXiv:0907.3740, 2009	369	2009
Unsupervised Cross-Dataset Transfer Learning for Person Re-Identification YT Peixi Peng, Tao Xiang, Yaowei Wang, Massimiliano Pontil, Shaogang Gong ... The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016	347*	2016
Oracle inequalities and optimal inference under group sparsity K Lounici, M Pontil, S Van De Geer, AB Tsybakov The annals of statistics 39 (4), 2164-2204, 2011	341	2011
Component-based face detection B Heiselet, T Serre, M Pontil, T Poggio Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision …, 2001	296	2001
Face detection in still gray images B Heisele, M Pontil MASSACHUSETTS INST OF TECH CAMBRIDGE MA CENTER FOR BIOLOGICAL AND …, 2000	296	2000

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