Philippe Rigollet
http://www-math.mit.edu/~ rigollet
Mathematics Department
Center for Statistics
Massachusetts Institute of Technology
Appointments
rigollet@math.mit.edu
Spring 2015-Present
Massachusetts Institute of Technology
Assistant Professor.
2008-2014
Princeton University
Assistant Professor.
1/2007-6/2008
Georgia Institute of Technology
Visiting Assistant Professor (PostDoc).
Education
Université Paris–vi
2003-06
Ph.D. in Mathematical Statistics: Oracle inequalities, aggregation and adaptation.
Supervised by Alexandre Tsybakov.
Université Paris–vi
M. Sc. in Mathematical Statistics
M. Sc. in Actuarial Science
B. Sc. in Applied Mathematics
B. Sc. in Statistics
2003
2003
2002
2002
Grants
NSF grant DMS-1317308 (PI). $450K.
NSF CAREER award (PI). $400K.
NSF grant DMS-0906424 (PI). $110K.
Berkeley France Fund (co-PI). $8K.
Honors and
Awards
Professeur Invité at Université Paris–vii
Conference on Learning Theory: Best paper award
Howard B. Wentz Jr. Junior Faculty Award
The 250th Anniversary Fund for Innovation in Undergraduate Education
Professeur Invité at Ecole Normale Supérieure de Cachan
Princeton Engineering commendation list for outstanding teaching for ORF525
PhD fellowship from the French Ministry of Research and New Technologies
Ph.D. Students
Xin Tong
Quentin Berthet
Lu Xia
2012
2014
2015 (exp.)
2013-16
2011-16
2009-11
2006
Assistant Prof. at USC
Lecturer at U. of Cambridge in 2015
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2014
2013
2013
2010
2009
2009
2003
Teaching
At MIT:
18.S997– High Dimensional Statistics (S15)
At Princeton University:
ORF245–Fundamentals of Engineering statistics (F08, S10, S11, F11, F12)
ORF525–Statistical Learning Theory and Nonparametric Estimation (S09, S11, S12, S13)
ORF524–Statistical Theory and Methods (F09)
ORF566–High Dimensional Statistics (S14)
Introduction to MATLAB (F09-13)
Stochastic Analysis Seminar: Random Matrices (F12)
Stochastic Analysis Seminar: Random Graphs (S13)
Stochastic Analysis Seminar: Roots of Polynomials and Probability (F14)
At Georgia Tech:
Statistics and applications (S07, F07)
Testing statistical hypotheses (S08)
Conference
Publications
1. Optimal rates of sparse estimation and universal aggregation, (with A. Tsybakov).
(2010). Oberwolfach reports, 7(1), 924-927. In, Modern Nonparametric Statistics:
Going Beyond Asymptotic Minimax , March 2010.
2. Mirror averaging, aggregation and model selection, (with A. Juditsky and A. Tsybakov). (2005). Oberwolfach reports, 2(4), 2688-2691. In, Meeting on Statistical and
Probabilistic Methods of Model Selection, October 2005.
Peer Reviewed
Conference
Publications
3. Complexity theoretic lower bounds for sparse principal component detection (with Q.
Berthet). (2013). Conf. Learning Theory. Best paper award.
4. Bounded regret in stochastic multi-armed bandits (with S. Bubeck and V. Perchet).
(2013). Conf. Learning Theory.
5. Neyman-Pearson classification under a strict constraint, (with X. Tong). (2011). Conf.
Learning Theory.
6. Nonparametric bandit with covariates, (with A. Zeevi). (2010). Conf. Learning Theory.
Peer Reviewed
Journal
Publications
7. Optimal learning with Q-aggregation (with G. Lecué) (2014). Ann. Statist., 42(1),
211-224.
8. Aggregation of Affine Estimators, with D. Dai, L. Xia and T. Zhang (2014). Electronic
Journal of Statistics, 8, 302-327.
9. The multi-armed bandit problem with covariates (with V. Perchet) (2013). Ann.
Statist., 41(2), 693-721.
10. Optimal detection of sparse principal components in high dimension (with Q. Berthet)
(2013). Ann. Statist., 41(1), 1780-1815.
11. Estimation of Covariance Matrices under Sparsity Constraints (with A. Tsybakov)
(2012). Statistica Sinica. 22(4), 1358–1367.
12. Sparse Estimation by Exponential Weighting (with A. Tsybakov). (2012). Statist.
Sci., 27(4), 558-575.
13. Deviation Optimal Learning using Greedy Q-aggregation (with D. Dai and T. Zhang).
(2012). Ann. Statist., 40(3), 1878-1905.
14. Kullback-Leibler aggregation and misspecified generalized linear models. (2012). Ann.
Statist., 40(2), 639-665.
15. Neyman-Pearson classification, convexity and stochastic constraints, (with X. Tong).
(2011). Journal of Machine Learning Research, 12(Oct), 2831-2855.
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16. Exponential screening and optimal rates of sparse estimation, (with A. Tsybakov).
(2011). Ann. Statist., 39(2), 731-771.
17. Optimal rates for plug-in estimators of density level sets, (with R. Vert). (2009).
Bernoulli, 15(4), 1154-117.
18. Learning by mirror averaging, (with A. Juditsky and A. Tsybakov). (2008). Ann.
Statist., 36(5), 2183-2206.
19. Generalization error bounds in semi-supervised classification under the cluster assumption. (2007). Journal of Machine Learning Research, 8(Jul), 1369-1392.
20. Linear and convex aggregation of density estimators, (with A. Tsybakov). (2007).
Math. Methods of Statist., 15(3), 260-280.
21. Adaptive density estimation using the blockwise Stein method. (2006). Bernoulli,
12(2), 351-370.
22. Inégalités d’oracles pour l’estimation d’une densité de probabilité. (2005). C. R. Acad.
Sci. Paris, Ser. I, 340(1), 59-62.
Preprints
Invited talks
23. Estimation of Functionals of Sparse Covariance Matrices. (2014). with J. Fan and W.
Wang. ArXiv:1408.5087.
2015
2014
2013
2012
Conference on Big Data Theory, University College London
Statistics Seminar, University of Michigan
Machine Learning Seminar, Microsoft Research Redmond
Statistics Seminar, The George Washington University
Statistics Seminar, ENSAE-CREST, Paris
Probability Seminar, University Paris Descartes
ORIE Colloquium, Cornell University
Statistics Colloquium, University of Wisconsin-Madison
Statistics Seminar, Yale University
Statistics Colloquium, University of Chicago
IC Colloquium, EPFL, Switzerland
Statistics Seminar, CMS, California Institute of Technology
Statistics Seminar, SSC, UT Austin
Workshop: Systems Information Learning Optimization (panelist), UW Madison
Conference: European Meeting of Statisticians, Budapest
Decision Sciences Seminar, Fuqua School of Business, Duke University
Statistics Seminar, Statistics department, Cornell University
Colloquium, Microsoft Research NY
Workshop: Optimization and Statistical Learning, Les Houches
Statistics Seminar, Department of Statistics, University of Pennsylvania
SILO seminar, UW Madison
Stochastics and Applications Seminar, MIT
Mathematics and Statistics Colloquium, Boston University
International Symposium on Mathematical Programming, Berlin
Workshop: Meeting the Challenges of High Dimensions, IMS, Singapore
8th World Congress in Probability and Statistics, Istambul
Statistics Seminar, Yale University
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2011
2010
2009
2008
2007
2006
2005
2004
Workshop: Structural methods of data analysis and optimization, Moscow
Humboldt-Princeton Conference, Berlin
Statistics Seminar, Rutgers
Joint Statistical Meetings, Miami
Workshop: Mathematical and Computational Foundations of Learning Theory, Dagstuhl
Foundations of Computational Mathematics, Budapest
Conference on Learning Theory, Budapest
Workshop: Sparse statistics, Optimization and Machine Learning, Banff
Colloquium, Statistics Laboratory, University of Cambridge
Statistics Seminar, Statistics Laboratory, University of Cambridge
73rd Annual meeting of the IMS, Gothenburg
Conference on Learning Theory, Haifa
Workshop:Modern Massive Data Sets, Stanford University
Conference on Resampling methods and High Dimensional Data, Texas A&M University
FODAVA Forum, IEEE Visweek, Atlantic City
Stochastics Seminar, School of Mathematics, Georgia Institute of Technology
Statistics Seminar, Department of Statistics, University of Pennsylvania
Meeting on Mathematical Statistics, Luminy
Forschungsseminar Mathematische Statistik, WIAS, Berlin
Statistics Seminar, Department of Mathematics, MIT
Colloquium, Department of Statistics, Stanford University
Colloquium, Department of Statistics, Carnegie Mellon University
Colloquium, ORFE, Princeton University
Colloquium, Department of Computer Science, University of Chicago
Colloquium, Department of Statistics, Rutgers
Colloquium, Department of Statistics, University of Minnesota
Colloquium, Department of Mathematics, Clemson University
Colloquium, Department of Mathematics, Illinois Institute of Technology
Stochastics Seminar, School of Mathematics, Georgia Institute of Technology
Statistics Seminar, ISyE, Georgia Institute of Technology
Colloquium, Mathematics Department, UC San Diego
Seminar, Department of Statistics, UC Berkeley
Meeting on Mathematical Statistics, Luminy
Statistics Seminar, Institut de Mathématiques, Université Paul Sabatier, Toulouse
Seminar for Statistics and Stochastic Models, LJK, Université Joseph Fourier, Grenoble
Stochastic Models and Statistics Days, Lille
Machine Learning Working Group, Statistics Department, UC Berkeley
Stochastics Seminar, School of Mathematics, Georgia Institute of Technology
Machine Working Group, EECS, UC Berkeley
Meeting on Mathematics Statistics, Luminy
Forschungsseminar Mathematische Statistik, WIAS, Berlin
Meeting on Mathematics Statistics, Luminy
Statistics Seminar, Ecole Normale Superieure, Paris
Probability and Statistics Seminar, Université de Provence
Statistics Seminar, Technische Universität Braunschweig
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Professional
Activities
Associate Editor:
Journal of Statistical Planning and Inference, 2012-2015
Bernoulli, 2013-2016
Statistical Inference for Stochastic Processes, 2015-2016
Executive committee:
COLT steering committee (elected), 2013-2016
Program Committee:
3rd Princeton Day of Statistics, 2012
Conference on Learning Theory (COLT), 2012-15.
Meeting on Mathematical Statistics (France), 2012-14
Optimization and Statistical Learning (France), 2013, 15
International Workshop on Statistical Learning (Russia), 2013
Organization:
Conference on Learning Theory, Princeton, 2013
Princeton-Humboldt conference, Princeton, 2013
3rd Princeton Day of Statistics, Princeton, 2012
Meeting on Mathematical Statistics, Luminy, 2012-14
Optimization and Statistical Learning, Les Houches, 2013, 15
International Workshop on Statistical Learning, Moscow, 2013
Wilks statistics seminar, 2012Wilks distinguished lecture on statistics, Princeton, 2012-2014
Departmental Colloquium, 2012-13
Blackboard Sessions, Princeton University, 2013-2014
Datafest, Princeton University, 2014
Academic Advising:
BSE Freshmen academic advising, 2008-2014
ORFE academic advising, 2009-2014
Thesis Advising:
1 junior project
14 senior theses
Websites:
C=Conception, I=Implementation
http://orfe.princeton.edu
C
http://www.princeton.edu/~rigollet
C+I
http://orfe.princeton.edu/statlab
C+I
http://www.stat.iitp.ru
C+I
http://orfe.princeton.edu/conferences/ph13
C+I
http://orfe.princeton.edu/~rigollet/bbs
C+I
Local committees:
ORFE Faculty hiring Committee (2011-12)
ORFE Graduate students recruiting (2008-2013)
ORFE AI assignments (2012-2014)
Memberships:
American Mathematical Society
Association for Computational Machinery
Institute of Mathematical Statistics
Grant reviews:
Israel Science Foundation
National Security Agency
National Science Foundation (DMS, IIS)
Swiss National Science Foundation
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Paper reviews:
Annals of Statistics
Annals of the Institute of Statistical Mathematics
Annales de l’Institut Henri Poincaré
Bernoulli
Biometrika
Conference on Learning Theory (COLT)
Computational Statistics & Data Analysis
Constructive Approximation
Electronic Journal of Statistics
IEEE Transactions on Information Theory
IEEE Transactions on Neural Networks
International Conference on Artificial Intelligence and Statistics (AISTATS)
Journal of Computer and System Sciences
Journal of Machine Learning Research
Mathematical Methods of Statistics
Mathematical Reviews
Neural Information Processing Systems (NIPS)
Optimization Methods and Software
Pattern Recognition
PLOS ONE
Probability Theory and Related Fields
Signal Processing with Adaptive Sparse Structured Representations (SPARS)
SIAM Journal on Optimization
SIAM Journal on Imaging Sciences
Statistical Science
Statistical Sinica
Statistics and Probability Letters
Stochastic Systems
Symposium on the Theory of Computing (STOC)
Transactions on Pattern Analysis and Machine Intelligence
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