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
Michele DoniniHelsingVerified email at helsing.ai
Paolo FrasconiProfessor of Computer Science, Università di FirenzeVerified email at dsi.unifi.it
Saverio SalzoAssistant Professor, Sapienza University of Rome, ItalyVerified email at diag.uniroma1.it
Luca FranceschiAmazon Web ServicesVerified email at amazon.de
alessandro verriprofessor of computer science, dibris, università degli studi di genovaVerified email at unige.it
Bernardino Romera-ParedesGoogle DeepMindVerified email at google.com
Riccardo GrazziPost Doc, Italian Institute of TechnologyVerified email at iit.it
Luca OnetoDIBRIS - University of GenoaVerified email at unige.it
Karim LouniciStatistics Professor, Ecole PolytechniqueVerified email at polytechnique.edu
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
Andre ElisseeffGoogleVerified email at google.com
Yiming YingSchool of Mathematics and Statistics, University of SydneyVerified email at sydney.edu.au
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
Bernd HeiseleVerified email at mty.ai

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	1964	2004
Multi-task feature learning A Argyriou, T Evgeniou, M Pontil Advances in neural information processing systems 19, 41, 2007	1863	2007
Convex multi-task feature learning A Argyriou, T Evgeniou, M Pontil Machine learning 73, 243-272, 2008	1790	2008
Regularization networks and support vector machines T Evgeniou, M Pontil, T Poggio Advances in computational mathematics 13, 1-50, 2000	1667	2000
Feature selection for SVMs J Weston, S Mukherjee, O Chapelle, M Pontil, T Poggio, V Vapnik NIPS 12, 668-674, 2000	1567	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	1251	1998
Learning multiple tasks with kernel methods. T Evgeniou, CA Micchelli, M Pontil Journal of machine learning research 6 (4), 2005	1112	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	911	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	837	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	819	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	804	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	728	2011
On learning vector-valued functions CA Micchelli, M Pontil Neural computation 17 (1), 177-204, 2005	661	2005
Support vector machines: Theory and applications T Evgeniou, M Pontil Advanced course on artificial intelligence, 249-257, 1999	656	1999
Empirical bernstein bounds and sample variance penalization A Maurer, M Pontil arXiv preprint arXiv:0907.3740, 2009	580	2009
Predicting structured data G BakIr, T Hofmann, B Schölkopf, AJ Smola, B Taskar MIT press, 2007	553	2007
Learning the Kernel Function via Regularization. CA Micchelli, M Pontil Journal of machine learning research 6 (7), 2005	528	2005
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	517	2018
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	482	2018
Forward and reverse gradient-based hyperparameter optimization L Franceschi, M Donini, P Frasconi, M Pontil International Conference on Machine Learning, 1165-1173, 2017	480	2017

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