Section: Dissemination

Scientific Animations

Editorial boards

• A. d'Aspremont, Associate Editor, Optimization Methods & Software (2010-2014)

• A. d'Aspremont, Associate Editor, SIAM Journal on Optimization (2013-...)

• 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

Area chair

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

Workshop and conference organization

• A. d'Aspremont, Workshop preparation for les Houches in Jan 2015: Optimization and Statistical Learning, with Zaid Harchaoui, LEAR, Inria and LJK, Anatoli Juditsky, LJK, Université Joseph Fourier, Jérôme Malick, CNRS and LJK et Philippe Rigollet, ORFE, Princeton University, USA.

• A. d'Aspremont, session organized at SIOPT 2014 in San Diego.

• F. Bach, Workshop co-chair for NIPS 2014.

• V.Perchet, Organizer, summer school "Ecole d'été pluridisciplinaire de Théorie des Jeux", Aussois (7-13 September 2014).

Awards

• F. Bach, 10-year best paper award, ICML 2014.

• S. Lacoste-Julien, MCMCSKi IV Honorable Mention Poster Prize (January 2014).

Other

• A. d'Aspremont, Scientific committee, programme Gaspard Monge pour l'Optimisation.

Invited presentations

• S. Arlot, "Kernel change-point detection", Workshop "Kernel methods for big data" (Université Lille 1, March 31 - April 2, 2014)

• S. Arlot, "Optimal model selection with V-fold cross-validation: how should V be chosen?", Seventh International Conference on High Dimensional Probability (Institut d'Études Scientifiques de Cargèse, May 26-31, 2014).

• A. d'Aspremont, "Spectral Ranking using Seriation." Journée big data, SPOC seminar, LIP6, Université de Paris VI.

• A. d'Aspremont, "Spectral Ranking using Seriation." Workshop on Semidefinite Optimization, Approximation and Applications, Simons Institute, Berkeley, Sept. 2014.

• A. d'Aspremont, "Spectral Ranking using Seriation." Cambridge statistics seminar, November 2014.

• A. d'Aspremont, "Convex Relaxations for Permutation Problems." Oxford robotics seminar, March 2014

• A. d'Aspremont, "Convex Relaxations for Permutation Problems." Department of Mathematical Engineering seminar, UCL, Louvain-la-Neuve, February 2014.

• A. d'Aspremont, "Convex Relaxations for Permutation Problems." Colloque CNRS MASTODONS, January 2014.

• A. d'Aspremont, "Convex Relaxations for Permutation Problems." Lunteren Conference on the Mathematics of Operations Research, January 2014.

• A. d'Aspremont, "An Optimal Affine Invariant Smooth Minimization Algorithm." Lunteren Conference on the Mathematics of Operations Research, January 2014.

• A. d'Aspremont, "Phase Recovery, MaxCut and Complex Semidefinite Programming." SLAC Photon Science Seminar, Stanford, March 2014.

• A. d'Aspremont, "Optimisation et apprentissage." Colloquium Jacques Morgenstern, Inria Sophia-Antipolis, Avril 2014.

• F. Bach, Invited talk at workshop on stochastic gradient methods, IPAM, Los Angeles (February 2014).

• F. Bach, Seminar at University of Logano (March 2014).

• F. Bach, Invited tutorial at Eurandom Workshop, Eindhoven (March 2014).

• F. Bach, Invited talk at the Centre de Recerca Matemàtica (CRM), Barcelona (April 2014).

• F. Bach, Seminars at Oxford University (May 2014).

• F. Bach, Invited talk at "Journées de la SFDS", Rennes (June 2014).

• F. Bach, Invited talk at the conference CAP, Saint-Etienne (July 2014).

• F. Bach, Invited tutorial at the IFCAM Summer school, Bangalore, India (July 2014).

• F. Bach, Invited talk at the Duke/UCL workshop, London (September 2014).

• F. Bach, Keynote talk at the conference ECML, Nancy (September 2014).

• F. Bach, Seminar at the University of Vienna, Austria (November 2014).

• F. Bach, Invited talk at the Swiss Statistics Seminar, Berne (November 2014).

• F. Bach, Invited talk at the CIFAR meeting on Neural Computation & Adaptive Perception, Montreal, Canada (December 2014).

• N. Boumal, Journée conjointe des GDR, ISIS and MIA: optimisation géométrique sur les variétés, Nov. 21, Paris.

• N. Boumal, Bordeaux University GIO 2014 international workshop, on the Geometry of Information and Optimization, Dec. 4 & 5, Bordeaux.

• F. Fogel, “Convex Relaxations for Permutation Problems”, Journées MAS de Toulouse, August.

• F. Fogel, workshop “Algorithm and Data Science” at Microsoft Research Cambridge, May 15.

• S. Lacoste-Julien, "Frank-Wolfe optimization insights in machine learning", Tsinghua University, Beijing, China, June.

• S. Lacoste-Julien, "Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering", invited talk at Journées MAS 2014, Institut de Mathématiques de Toulouse, Toulouse, France, August.

• S. Lacoste-Julien, "Recent Advances in Frank-Wolfe Optimization", invited talk at the 4th IMA Conference on Numerical Linear Algebra and Optimisation, Birmingham, UK, September.

• S. Lacoste-Julien, "Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering", McGill University, Montreal, Canada, December.

• R. Lajugie, invitation at the workshop "Kernel methods for big data" in Lille (March, 31st -April, 2nd).

• V. Perchet, Workshop "Optimal Cooperation, Communication, and Learning in Decentralized Systems", Banff, Canada (October 16, 2014). Blackwell Approachability in Absorbing Games.

• V. Perchet, Conference "PGMO-COPI", Paris (October 28, 2014). Online multiclass classification via Blackwell approachability.

• V. Perchet, Conference "PGMO-COPI", Paris (October 30, 2014). New results in bandits problems with applications.

• V. Perchet, Séminaire probas/stats, Orsay (December 4, 2014). From Bandits to Ethical Clinical Trials. Optimal Sample Size for Multi-Stage Problems.

• V. Perchet, Conference "New Procedures for New Data", CIRM, Marseille (December 15, 2014). From Bandits to Ethical Clinical Trials. Optimal Sample Size for Multi-Stage Problems.

• N. Shervashidze, "Representing graphs for machine learning", Séminaire de Statistiques, Institut Henri Poincaré, Paris, June.