Section: Dissemination
Promoting Scientific Activities
Scientific Events Organisation
General Chair, Scientific Chair
Member of the Organizing Committees

Adrian Taylor, Session Organizer: Computerassisted analyses of optimization algorithms I & II, International Symposium on Mathematical Programming, July 2018.

F. Bach: Coorganization of the workshop “Horizon Maths 2018 : Intelligence Artificielle”, November 23, 2018
Scientific Events Selection
Chair of Conference Program Committees
Reviewer

Conference on Learning Theory (COLT 2018): Pierre Gaillard, Alessandro Rudi

Symposium on Discrete Algorithms (SODA 2019): Adrien Taylor,

Neural Information Processing Systems (NIPS 2018): Pierre Gaillard, Alessandro Rudi

Conference on Learning Theory (COLT 2018): Pierre Gaillard, Alessandro Rudi, Adrien Taylor

International Conference of Machine Learning (ICML 2018): Pierre Gaillard, Alessandro Rudi
Journal
Member of the Editorial Boards

F. Bach: Journal of Machine Learning Research, coeditorinchief

F. Bach: Electronic Journal of Statistics, Associate Editor.

F. Bach: Foundations of Computational Mathematics, Associate Editor.

A. d’Aspremont: SIAM Journal on Optimization, Associate editor

A. d’Aspremont: SIAM Journal on the Mathematics of Data Science, Associate Editor
Reviewer  Reviewing Activities

Journal of Optimization Theory and Algorithms: Adrien Taylor

Journal of Machine Learning Research: Pierre Gaillard, Alessandro Rudi
Invited Talks

F. Bach, Trends in Optimization Seminar, University of Washington, November 2018.

Pierre Gaillard. Distributed averaging of observations in a graph: the gossip problem. MNL Conference, Paris, November 2018.

Adrien Taylor, Analysis and design of firstorder methods via semidefinite programming, Seminaire Parisien dOptimisation (SPO), Paris (France), November 2018.

F. Bach, Frontier Research and Artificial Intelligence, European Research Council, Brussels, October 2018.

F. Bach, IDSS Distinguished Speaker Seminar, MIT, October 2018.

F. Bach, Mathematical Institute Colloquium, Oxford, October 2018.

Adrien Taylor, Convex Interpolation and Performance Estimation of First order Methods for Convex Optimization, IBM/FNRS innovation award, Brussels (Belgium), October 2018.

F. Bach, Workshop on Structural Inference in HighDimensional Models, Moscow, September 2018.

F. Bach, Symposium on Mathematical Programming (ISMP), Bordeaux, plenary talk, July 2018.

Alexandre d'Aspremont, Sharpness, Restart and Compressed Sensing Performance, ISMP 2018, Bordeaux, July 2018.

Alessandro Rudi, FALKON: An optimal method for large scale learning with statistical guarantees, ISMP 2018, Bordeaux, July 2018.

Adrien Taylor, Computerassisted Lyapunovbased worstcase analyses of first order methods, International Symposium on Mathematical Programming, Bordeaux (France), July 2018.

F. Bach, SIAM Conference on Imaging Science, Bologna, Italy, invited talk, June 2018.

Pierre Gaillard. Online prediction of arbitrary timeseries with application to electricity consumption. Conference on nonstationarity. Cergy Pontoise University. June 2018.

Adrien Taylor, Convex Interpolation and Performance Estimation of Firstorder Methods for Convex Optimization, International Symposium on Mathematical Programming: Tucker prize finalist, Bordeaux (France), July 2018.

Alexandre d'Aspremont, An approximate ShapleyFolkman Theorem, Isaac Newton Institute, Cambridge, June 2018.

F. Bach,Workshop on Future challenges in statistical scalability, Newton Institute, Cambridge, UK, June 2018.

Adrien Taylor, Automated design of firstorder optimization methods, Operation Research Seminar, UCLouvain, LouvainlaNeuve (Belgium), May 2018.

Adrien Taylor, Automated design of firstorder optimization methods, LCCC Control Seminar, Lund University, Lund (Sweden), May 2018.

Pierre Gaillard. Distributed learning with orthogonal polynomials. Inria DGA meetup. May 2018.

F. Bach, Workshop on Optimisation and Machine Learning in Economics, London, March 2018.

Pierre Gaillard. An overview of Artificial Intelligence. Hackaton. PSL University. March 2018.

Alexandre d'Aspremont, Regularized Nonlinear Acceleration, US and Mexico Workshop on Optimization and its Applications, Jan 2018.

Alessandro Rudi, Learning with Random Features, Isaac Newton Institute, Cambridge, Jan 2018.

Pierre Gaillard. Online nonparametric regression with adversarial data. Smile seminar. Paris. Jan 2018.