Massimiliano Pontil

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TOMASO POGGIOMcDermott Professor in Brain Sciences, MITEmail yang diverifikasi di ai.mit.edu
Andreas ArgyriouMicrosoft UKEmail yang diverifikasi di alum.mit.edu
Carlo CilibertoUniversity College LondonEmail yang diverifikasi di ucl.ac.uk
Michele DoniniHelsingEmail yang diverifikasi di helsing.ai
Paolo FrasconiProfessor of Computer Science, Università di FirenzeEmail yang diverifikasi di dsi.unifi.it
Saverio SalzoAssistant Professor, Sapienza University of Rome, ItalyEmail yang diverifikasi di diag.uniroma1.it
Luca FranceschiAmazon Web ServicesEmail yang diverifikasi di amazon.de
alessandro verriprofessor of computer science, dibris, università degli studi di genovaEmail yang diverifikasi di unige.it
Riccardo GrazziPost Doc, Italian Institute of TechnologyEmail yang diverifikasi di iit.it
Bernardino Romera-ParedesGoogle DeepMindEmail yang diverifikasi di google.com
Karim LouniciStatistics Professor, Ecole PolytechniqueEmail yang diverifikasi di polytechnique.edu
Luca OnetoDIBRIS - University of GenoaEmail yang diverifikasi di unige.it
Mark HerbsterUniversity College LondonEmail yang diverifikasi di cs.ucl.ac.uk
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindEmail yang diverifikasi di gatsby.ucl.ac.uk
Luca BaldassarreAI Governance Director, Swiss ReEmail yang diverifikasi di swissre.com
Andre ElisseeffGoogleEmail yang diverifikasi di google.com
Vladimir R. KosticFaculty of Science, Novi Sad; IIT, Genova, ItalyEmail yang diverifikasi di dmi.uns.ac.rs
Pietro NovelliPostdoctoral Researcher, Italian Institute of TechnologyEmail yang diverifikasi di iit.it
Yiming YingSchool of Mathematics and Statistics, University of SydneyEmail yang diverifikasi di sydney.edu.au
Cecilia MascoloUniversity of CambridgeEmail yang diverifikasi di cl.cam.ac.uk

Ikuti

Massimiliano Pontil

Istituto Italiano di Tecnologia & University College London

Email yang diverifikasi di iit.it - Beranda

Applied Mathematics Learning Theory Machine Learning Statistics


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Regularized multi--task learning T Evgeniou, M Pontil Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004	2001	2004
Multi-task feature learning A Argyriou, T Evgeniou, M Pontil Advances in neural information processing systems 19, 41, 2007	1881	2007
Convex multi-task feature learning A Argyriou, T Evgeniou, M Pontil Machine learning 73, 243-272, 2008	1808	2008
Regularization networks and support vector machines T Evgeniou, M Pontil, T Poggio Advances in computational mathematics 13, 1-50, 2000	1681	2000
Feature selection for SVMs J Weston, S Mukherjee, O Chapelle, M Pontil, T Poggio, V Vapnik NIPS 12, 668-674, 2000	1579	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	1256	1998
Learning multiple tasks with kernel methods. T Evgeniou, CA Micchelli, M Pontil Journal of machine learning research 6 (4), 2005	1123	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	915	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	882	2018
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	856	2012
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	844	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	701	1999
On learning vector-valued functions CA Micchelli, M Pontil Neural computation 17 (1), 177-204, 2005	682	2005
Empirical bernstein bounds and sample variance penalization A Maurer, M Pontil arXiv preprint arXiv:0907.3740, 2009	604	2009
Predicting structured data G BakIr, T Hofmann, B Schölkopf, AJ Smola, B Taskar MIT press, 2007	558	2007
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	553	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	538	2018
Learning the Kernel Function via Regularization. CA Micchelli, M Pontil Journal of machine learning research 6 (7), 2005	531	2005
Forward and reverse gradient-based hyperparameter optimization L Franceschi, M Donini, P Frasconi, M Pontil International Conference on Machine Learning, 1165-1173, 2017	526	2017

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