Section: Dissemination

Scientific Animation

Editorial boards

• F. Bach: Journal of Machine Learning Research, Action Editor.

• F. Bach: IEEE Transactions on Pattern Analysis and Machine Intelligence, Associate Editor.

• F. Bach: Information and Inference, Associate Editor.

• F. Bach: SIAM Journal on Imaging Sciences, Associate Editor.

• F. Bach: International Journal of Computer Vision, Associate Editor

• A. d'Aspremont: Optimization Methods and Software

• A. d'Aspremont: SIAM Journal on Optimization

Area chair

• F. Bach: International Conference on Machine Learning, 2013

• F. Bach: Neural Information Processing Systems, 2013

Workshop and conference organization

• S. Arlot, member of the program committee of the Second Workshop on Industry & Practices for Forecasting (WIPFOR), EDF R&D, Clamart. 5-7 June 2013.

• A. d'Aspremont was co-organizer of the workshop on optimization and machine learning at Les Houches in Janurary 2013.

• F. Bach organized a workshop on "Big data: theoretical and practical challenges" - May, 14-15, 2013 - Institut Poincaré (co-organized with Michael Jordan), funded by the Fondation de Sciences Mathématiques de Paris and Inria.

• F. Bach and Michael Jordan coorganized the "Fête Parisienne in Computation, Inference and Optimization: A Young Researchers' Forum". A workshop organized in the framework of the the Schlumberger Chair for mathematical sciences at IHÉS. March 20, 2013. http://www.di.ens.fr/~fbach/ihes.html

• F. Bach also coorganized the "Workshop on "Succinct Data Representations and Applications", Theoretical Foundations of Big data. Simons Institute, Berkeley, September 2013.

Other

• S. Arlot is member of the board for the entrance exam in Ecole Normale Supérieure (mathematics, voie B/L).

• A. d'Aspremont is a member of the scientific committee of the programme Gaspard Monge pour l'optimisation (PGMO).

• A. d'Aspremont is a member of the scientific committee of Thales Alenia Space.

Invited presentations

• S. Arlot, "Kernel change-point detection", Workshop "Non-stationarity in Statistics and Risk Management" (CIRM, Marseille, January, 21-25, 2013).

• S. Arlot, "Sélection de modèles par validation croisée et sélection de paramètres pour la régression ridge et le Lasso", Groupe de Travail Neurospin-Select (Saclay, February, 20, 2013).

• S. Arlot, "Optimal model selection with V-fold cross-validation: how should V be chosen?", Fête Parisienne in Computation, Inference and Optimization: A Young Researchers' Forum (IHES, Bures-sur-Yvette, March, 20, 2013).

• S. Arlot, "Kernel change-point detection", Groupe de Travail de Statistique de Jussieu (Paris, November, 11, 2013).

• S. Arlot, "Analyse du biais de forêts purement aléatoires", Séminaire de l'Equipe de Probabilités et Statistiques (Institut Elie Cartan, Nancy, November, 28, 2013).

• S. Arlot, "Optimal data-driven estimator selection with minimal penalties", keynote lecture, Workshop "Mathematical Statistics with Applications in Mind" (CIRM, Marseille, December, 9-13, 2013).

• Simon Lacoste-Julien, "Harnessing the structure of data for discriminative machine learning":

  • Department of Statistics, University of Oxford, February 2013

  • Intelligent Systems Lab Amsterdam, University of Amsterdam, February 2013

  • Département d'informatique, Université de Sherbrooke, April 2013

  • School of Computer Science, McGill University, April 2013

  • Département d'Informatique, École Normale Supérieure, April 2013

• "Block-Coordinate Frank-Wolfe Optimization for Structured SVMs"

  • ICML, Atlanta, USA, June 2013

  • ICCOPT, Lisbon, Portugal, July 2013

• Simon Lacoste-Julien, "SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases", KDD, Chicago, August 2013

• Simon Lacoste-Julien, "Frank-Wolfe optimization insights in machine learning"

  • Département d'informatique, Université de Sherbrooke, August 2013

  • SMILE seminar, Paris, November 2013

  • SAIL meeting, UC Berkeley, December 2013

  • CILVR Lab , New York University, December 2013

  • Machine Learning Lab, Columbia University, December 2013

  • Reasoning and Learning Lab, McGill University, December 2013

• Simon Lacoste-Julien, "Making Sense of Big Data", CaFFEET, Stanford University, November

• Michael Jordan, Keynote Speaker, ACM Conference on Knowledge Discovery and Data Mining (SIGKDD), Beijing, China, 8/15/12

• Michael Jordan, Keynote Speaker, 21st Century Computing Conference, Tianjin, China, 10/25/12

• Michael Jordan, Keynote Speaker, ICONIP, Doha, Qatar, 11/12/12

• Michael Jordan, Invited Speaker, SAMSI Workshop on Massive Data Analysis, 9/9/12

• Michael Jordan, Invited Speaker, Méthodes Bayésiennes non Paramétriques pour le Traitement du

• Michael Jordan, Signal et des Images, Telecom ParisTech, Paris, France, 9/8/12

• Michael Jordan, Invited Speaker, Seminaire Parisien de Statistique, Paris, France, 9/17/12

• Michael Jordan, Invited Speaker, Workshop on Random Matrices and their Applications, Paris, France, 10/9/12

• Michael Jordan, Colloquium, Department of Informatique, Ecole Normale Superieure, 10/2/12

• Michael Jordan, Vincent Meyer Colloquium, Israel Institute of Technology, 11/5/12

• Michael Jordan, Invited Speaker, Workshop on Optimization and Statistical Learning, Les Houches, France, 1/8/13

• Michael Jordan, Harry Nyquist Lecture, Department of Electrical Engineering, Yale, 1/23/13

• Michael Jordan, Invited Speaker, Simons Workshop on Big Data, New York, 1/24/13

• Michael Jordan, Keynote Speaker, Workshop on Nonsmooth Optimization in Machine Learning, Liege, Belgium, 3/4/13

• Michael Jordan, Keynote Speaker, StatLearn Workshop, Bordeaux, France, 4/8/13

• Michael Jordan, Lecture Series, Ecole Nationale de la Statistique et de l'Administration, Paris, 5/13

• Michael Jordan, Keynote Speaker, Amazon Machine Learning Conference, Seattle, 4/28/13

• Michael Jordan, Keynote Speaker, Bayesian Nonparametrics Workshop, Amsterdam, 6/10/13

• Michael Jordan, Invited Speaker, Workshop on High-Dimensional Statistics, Moscow, 6/26/13

• Michael Jordan, Distinguished Lecture, Department of Statistics, University of Oxford, 5/7/13

• Michael Jordan, Colloquium, Department of Statistics, University of Cambridge, 5/10/13

• Michael Jordan, Invited Speaker, GdR ISIS Conference, Telecom ParisTech, Paris 5/16/13

• Matthieu Solnon, "Analysis of the oracle risk in multi-task kernel ridge regression", Colloque Statistique Mathématique et Applications, Fréjus, France.

• Mark Schmidt, "Opening up the black box: Faster methods for non-smooth and big-data optimization problems". Invited talk at DeepMind Technologies, London (June 2013).

• Mark Schmidt, "Linearly-Convergent Stochastic-Gradient Methods". Invited talk at Paris 6, Paris (June 2013).

• Mark Schmidt, "Minimizing Finite Sums with the Stochastic Average Gradient Algorithm". "Invited" talk at ICCOPT, Lisbon (July 2013).

• Edouard Grave, Alpage, Inria / Paris 7, May 2013

• Edouard Grave, Criteo, September 2013

• Edouard Grave, Laboratoire de Science Cognitive et Psycholinguistique, EHESS / ENS / CNRS, November 2013

• Alexandre d'Aspremont, "Convex Relaxations for Permutation Problems"

  • Workshop on Succinct Data Representations and Applications, Simons Institute, Berkeley, Sept. 2013.

  • Workshop MAORI, Ecole Polytechnique, Nov. 2013.

• Alexandre d'Aspremont, "Phase Retrieval, MAXCUT and Complex Semidefinite Programming"

  • GdT CEREMADE, Paris Dauphine, April 2013.

  • Journée du GdR ISIS, Telecom, May 2013.

  • Journée du GdR MOA, June 2013.

• Alexandre d'Aspremont,"Approximation Bounds for Sparse PCA"

  • Workshop on Structured families of functions and applications, Oberwolfach, February 2013.

  • PACM seminar, Princeton, USA, February 2013.

  • Séminaire ENSAE, France, April 2013.

  • Big Data workshop, IHP, May 2013.

• Alexandre d'Aspremont, "An Optimal Affine Invariant Smooth Minimization Algorithm", International Workshop on Statistical Learning, Moscow, June 2013.

• F. Bach: Optimization and Statistical Learning, January 6 - 11, 2013. Les Houches, France (Invited presentation)

• F. Bach: international biomedical and astronomical signal processing (BASP) Frontiers workshop, January 2013 (Invited presentation)

• F. Bach: Convex Relaxation Methods for Geometric Problems in Scientific Computing, IPAM, Los Angeles, February 2013 (Invited presentation)

• F. Bach: Nonsmooth optimization in machine learning. March 04, 2013, University of Liège (Invited presentation)

• F. Bach: Microsoft Research Machine Learning Summit: April 22-24, 2013 (Invited presentation)

• F. Bach: International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications, July 8 - 10, 2013, Leuven, Belgium (Invited presentation)

• F. Bach: European Conference on Dana Analysis, Luxembourg, July 2013 (Invited presentation)

• F. Bach: European Meeting of Statisticians (EMS), Budapest, Hungary, 20-25 July 2013 (Invited presentation)

• F. Bach: Fourth Cargese Workshop on Combinatorial Optimization. Institut d'Etudes Scientifiques de Cargèse, Corsica (France). September 30 - October 5, 2013 (Invited presentation)

• F. Bach: 9èmes Journées Nationales de la Recherche en Robotique, Annecy, October 16-18, 2013 (invited presentation)

• F. Bach: Radboud University, Nijmegen, Nederlands, November 29, 2013 (Seminar)

• F. Bach: GlobalSIP: IEEE Global Conference on Signal and Information Processing, December 3-5, 2013 (invited presentation)

• F. Bach: NIPS workshops, december 2013 (2 invited presentations)