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
Carlo CilibertoUniversity College LondonVerified email at ucl.ac.uk
Paolo FrasconiProfessor of Computer Science, Università di FirenzeVerified email at dsi.unifi.it
Michele DoniniHelsingVerified email at helsing.ai
Luca FranceschiAmazon Web ServicesVerified email at amazon.de
Saverio SalzoAssistant Professor, Sapienza University of Rome, ItalyVerified email at diag.uniroma1.it
alessandro verriprofessor of computer science, dibris, università degli studi di genovaVerified email at unige.it
Riccardo GrazziMicrosoft ResearchVerified email at microsoft.com
Bernardino Romera-ParedesGoogle DeepMindVerified email at google.com
Karim LouniciStatistics Professor, Ecole PolytechniqueVerified email at polytechnique.edu
Luca OnetoDIBRIS - University of GenoaVerified email at unige.it
Mark HerbsterUniversity College LondonVerified email at cs.ucl.ac.uk
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindVerified email at gatsby.ucl.ac.uk
Luca BaldassarreAI Governance Director, Swiss ReVerified email at swissre.com
Cecilia MascoloUniversity of CambridgeVerified email at cl.cam.ac.uk
Anastasios NoulasNew York University, Center for Data ScienceVerified email at cl.cam.ac.uk
Andre ElisseeffGoogleVerified email at google.com
Vladimir R. KosticFaculty of Science, Novi Sad; IIT, Genova, ItalyVerified email at dmi.uns.ac.rs
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


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Regularized multi--task learning T Evgeniou, M Pontil Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004	2007	2004
Multi-task feature learning A Argyriou, T Evgeniou, M Pontil Advances in neural information processing systems 19, 41, 2007	1890	2007
Convex multi-task feature learning A Argyriou, T Evgeniou, M Pontil Machine learning 73, 243-272, 2008	1798	2008
Regularization networks and support vector machines T Evgeniou, M Pontil, T Poggio Advances in computational mathematics 13, 1-50, 2000	1691	2000
Feature selection for SVMs J Weston, S Mukherjee, O Chapelle, M Pontil, T Poggio, V Vapnik NIPS 12, 668-674, 2000	1590	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	1259	1998
Learning multiple tasks with kernel methods. T Evgeniou, CA Micchelli, M Pontil Journal of machine learning research 6 (4), 2005	1124	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	921	2012
Bilevel programming for hyperparameter optimization and meta-learning L Franceschi, P Frasconi, S Salzo, R Grazzi, M Pontil arXiv preprint arXiv:1806.04910, 2018	905	2018
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 25, 2012	855	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	848	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 …, 2011	732	2011
Support vector machines: Theory and applications T Evgeniou, M Pontil Advanced course on artificial intelligence, 249-257, 1999	721	1999
On learning vector-valued functions CA Micchelli, M Pontil Neural computation 17 (1), 177-204, 2005	687	2005
Empirical bernstein bounds and sample variance penalization A Maurer, M Pontil arXiv preprint arXiv:0907.3740, 2009	614	2009
Empirical risk minimization under fairness constraints M Donini, L Oneto, S Ben-David, JS Shawe-Taylor, M Pontil Advances in neural information processing systems 31, 2018	566	2018
Predicting structured data G BakIr, T Hofmann, B Schölkopf, AJ Smola, B Taskar MIT press, 2007	563	2007
Quantum machine learning: a classical perspective C Ciliberto, M Herbster, AD Ialongo, M Pontil, A Rocchetto, S Severini, ... Proc. R. Soc. A 474 (2209), 20170551, 2018	555	2018
Forward and reverse gradient-based hyperparameter optimization L Franceschi, M Donini, P Frasconi, M Pontil International conference on machine learning, 1165-1173, 2017	546	2017
Learning the Kernel Function via Regularization. CA Micchelli, M Pontil Journal of machine learning research 6 (7), 2005	529	2005

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