Alexandre d'Aspremont - Google Scholar Citations

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Citations	4950	3181
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Co-authors

Laurent El GhaouiUC Berkeley (EECS, IEOR)Verified email at berkeley.edu
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
Michael I. JordanProfessor of EECS and Professor of Statistics, University of California, BerkeleyVerified email at cs.berkeley.edu
Gert LanckrietProfessor, UCSDVerified email at eng.ucsd.edu
Damien ScieurSamsung - SAIL MontréalVerified email at samsung.com
Vincent RouletPostdoc ADSI, University of Washington, SeattleVerified email at uw.edu
Stephane MallatProfesseur de Mathématiques Appliquées et Informatique, École Normale SupérieureVerified email at ens.fr
Marco CuturiGoogle Brain / CREST-ENSAE.Verified email at google.com
Rodolphe JENATTONSenior machine learning scientist at Google Brain, BerlinVerified email at google.com
Stephen BoydProfessor of Electrical Engineering, Computer Science, and Management Science, StanfordVerified email at stanford.edu
Selin Damla AhipasaogluAssistant Professor in Engineering Systems and Design, SUTDVerified email at sutd.edu.sg
Jean-Philippe VertGoogle Brain / Mines ParisTechVerified email at mines-paristech.fr
Joshua J. TurnerLinac Coherent Light SourceVerified email at slac.stanford.edu
Edouard OyallonCNRS, LIP6Verified email at lip6.fr
Antoine RecanatiPhD candidate, CNRS & Ecole Normale SupérieureVerified email at ens.fr
Martin JaggiEPFLVerified email at epfl.ch
Cristobal GuzmanUniversidad Católica de ChileVerified email at uc.cl
Milan VojnovicProfessor, Department of Statistics, LSEVerified email at lse.ac.uk
Nicolas BoumalPrinceton UniversityVerified email at math.princeton.edu
Raghu BollapragadaArgonne National LaboratoryVerified email at anl.gov

Alexandre d'Aspremont

CNRS & Ecole Normale Supérieure, Paris

Verified email at di.ens.fr - Homepage

Optimization machine learning finance.


Title	Cited by	Year
Model selection through sparse maximum likelihood estimation for multivariate Gaussian or binary data O Banerjee, LE Ghaoui, A d’Aspremont Journal of Machine learning research 9 (Mar), 485-516, 2008	1263	2008
A direct formulation for sparse PCA using semidefinite programming A d'Aspremont, LE Ghaoui, MI Jordan, GR Lanckriet Advances in neural information processing systems, 41-48, 2005	905	2005
Phase recovery, maxcut and complex semidefinite programming I Waldspurger, A d’Aspremont, S Mallat Mathematical Programming 149 (1-2), 47-81, 2015	418	2015
First-order methods for sparse covariance selection A d'Aspremont, O Banerjee, L El Ghaoui SIAM Journal on Matrix Analysis and Applications 30 (1), 56-66, 2008	323	2008
Optimal solutions for sparse principal component analysis A d’Aspremont, F Bach, LE Ghaoui Journal of Machine Learning Research 9 (Jul), 1269-1294, 2008	315	2008
Convex optimization techniques for fitting sparse Gaussian graphical models O Banerjee, LE Ghaoui, A d'Aspremont, G Natsoulis Proceedings of the 23rd international conference on Machine learning, 89-96, 2006	171	2006
Relaxations and randomized methods for nonconvex QCQPs A d’Aspremont, S Boyd EE392o Class Notes, Stanford University 1, 1-16, 2003	158	2003
Smooth optimization with approximate gradient A d'Aspremont SIAM Journal on Optimization 19 (3), 1171-1183, 2008	134	2008
Support vector machine classification with indefinite kernels R Luss, A d'Aspremont Advances in Neural Information Processing Systems, 953-960, 2008	126	2008
Testing the nullspace property using semidefinite programming A d’Aspremont, L El Ghaoui Mathematical programming 127 (1), 123-144, 2011	94	2011
Predicting abnormal returns from news using text classification R Luss, A d’Aspremont Quantitative Finance 15 (6), 999-1012, 2015	89	2015
Convex relaxations for permutation problems F Fogel, R Jenatton, F Bach, A d'Aspremont Advances in Neural Information Processing Systems, 1016-1024, 2013	76	2013
Static arbitrage bounds on basket option prices A d'Aspremont, L El Ghaoui Mathematical programming 106 (3), 467-489, 2006	73	2006
Identifying small mean-reverting portfolios A d'Aspremont Quantitative Finance 11 (3), 351-364, 2011	72	2011
Sparse PCA: Convex relaxations, algorithms and applications Y Zhang, A d’Aspremont, L El Ghaoui Handbook on Semidefinite, Conic and Polynomial Optimization, 915-940, 2012	60	2012
Phase retrieval for imaging problems F Fogel, I Waldspurger, A d’Aspremont Mathematical programming computation 8 (3), 311-335, 2016	54	2016
Full regularization path for sparse principal component analysis A d'Aspremont, FR Bach, LE Ghaoui Proceedings of the 24th international conference on Machine learning, 177-184, 2007	54	2007
Regularized nonlinear acceleration D Scieur, A d'Aspremont, F Bach Advances In Neural Information Processing Systems, 712-720, 2016	50	2016
Clustering and feature selection using sparse principal component analysis R Luss, A d’Aspremont Optimization and Engineering 11 (1), 145-157, 2010	43	2010
Sharpness, restart and acceleration V Roulet, A d'Aspremont Advances in Neural Information Processing Systems, 1119-1129, 2017	35	2017

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