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 DoniniAmazonVerified email at amazon.com
Luca FranceschiAmazon Web ServicesVerified email at amazon.de
alessandro verriprofessor of computer science, dibris, università degli studi di genovaVerified email at unige.it
Saverio SalzoAssistant Professor, Sapienza University of Rome, ItalyVerified email at diag.uniroma1.it
Bernardino Romera-ParedesGoogle DeepMindVerified email at google.com
Mark HerbsterUniversity College LondonVerified email at cs.ucl.ac.uk
Luca OnetoDIBRIS - University of GenoaVerified email at unige.it
Luca BaldassarreLead Data Scientist, Swiss ReVerified email at swissre.com
Riccardo GrazziIIT, UCLVerified email at iit.it
Andre ElisseeffGoogleVerified email at google.com
Arthur GrettonGatsby Computational Neuroscience Unit and DeepmindVerified 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
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


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	1848	2004
Multi-task feature learning A Argyriou, T Evgeniou, M Pontil Advances in neural information processing systems 19, 41, 2007	1731	2007
Convex multi-task feature learning A Argyriou, T Evgeniou, M Pontil Machine learning 73, 243-272, 2008	1693	2008
Regularization networks and support vector machines T Evgeniou, M Pontil, T Poggio Advances in computational mathematics 13, 1-50, 2000	1593	2000
Feature selection for SVMs J Weston, S Mukherjee, O Chapelle, M Pontil, T Poggio, V Vapnik NIPS 12, 668-674, 2000	1525	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	1223	1998
Learning multiple tasks with kernel methods. T Evgeniou, CA Micchelli, M Pontil Journal of machine learning research 6 (4), 2005	1060	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	853	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	775	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	705	2011
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	615	2012
On learning vector-valued functions CA Micchelli, M Pontil Neural computation 17 (1), 177-204, 2005	584	2005
Bilevel programming for hyperparameter optimization and meta-learning L Franceschi, P Frasconi, S Salzo, R Grazzi, M Pontil arXiv preprint arXiv:1806.04910, 2018	535	2018
Predicting structured data G BakIr, T Hofmann, B Schölkopf, AJ Smola, B Taskar MIT press, 2007	516	2007
Learning the Kernel Function via Regularization. CA Micchelli, M Pontil Journal of machine learning research 6 (7), 2005	499	2005
Empirical bernstein bounds and sample variance penalization A Maurer, M Pontil arXiv preprint arXiv:0907.3740, 2009	462	2009
Support vector machines: Theory and applications T Evgeniou, M Pontil Machine Learning and Its Applications: Advanced Lectures, 249-257, 2001	436	2001
Advances in large margin classifiers AJ Smola, PJ Bartlett, D Schuurmans, B Schölkopf MIT press, 2000	418	2000
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	414*	2016
Oracle inequalities and optimal inference under group sparsity K Lounici, M Pontil, S Van De Geer, AB Tsybakov	383	2011

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