Section: Dissemination

Promoting Scientific Activities

Scientific Events Organisation

• P. Germain and F. Bach: co-organization of NIPS workshop: "(Almost) 50 Shades of Bayesian Learning: PAC-Bayesian trends and insights" https://bguedj.github.io/nips2017/50shadesbayesian.html

• A. d'Aspremont: co-organization of the workshop: “Optimization and Statistical Learning”, Les Houches, France

Member of the Organizing Committees

• F. Bach: Senior Area chair for NIPS 2017

Journal

Member of the Editorial Boards

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

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

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

• F. Bach: Mathematical Programming, Associate Editor.

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

• A. d'Aspremont: SIAM Journal on Optimization, Associate Editor.

Invited Talks

• F. Bach: Workshop on Shape, Images and Optimization, Muenster, Germany invited talk, February 2017

• F. Bach: SIAM conference on Optimization, Vancouver, Canada, invited tutorial, May 2017

• F. Bach: LCCC workshop on Large-Scale and Distributed Optimization, Lund, Sweden, invited talk, June 2017

• F. Bach: Summer school on Structured Regularization for High-Dimensional Data Analysis, Paris, invited talk, June 2017

• F. Bach: FOCM Barcelona, two invited talks in special sessions, July 2017

• F. Bach: European Signal Processing conference (EUSIPCO), Kos, Greece, keynote speaker, August 2017

• F. Bach: StatMathAppli 2017, Frejus, mini-course on optimization, September 2017

• F. Bach: 2017 ERNSI Workshop on System Identification, Lyon, invited plenary talk, September 2017

• F. Bach: New-York University, Data science seminar, October 2017

• F. Bach: Workshop on Generative models, parameter learning and sparsity, Cambridge, UK, invited talk, November 2017

• F. Bach: NIPS workshops, two invited talks, Long Beach, CA, December 2017

• A. d'Aspremont: “Regularized Nonlinear Acceleration”

  • GdR MOA, Bordeaux.

  • GdR MEGA, Paris.

  • SIAM OPtimization conference

  • Oxford computational math seminar

  • Alan Turing institute

• A. d'Aspremont: “Sharpness, Restart and Acceleration”. Foundations of Computational Mathematics, Barcelona.

• P. Germain: “Generalization of the PAC-Bayesian Theory, and Applications to Semi-Supervised Learning”, Modal Seminars, Lille, France, January 2017

• P. Germain: “Theory Driven Domain Adaptation Algorithm”, Google Brain TechTalk, Mountain View (CA), USA, April 2017

• P. Gaillard: “Sparse acceleration of exponential weights”

  • Seminar of the SEQUEL project team, Lilles, February 2017

  • 49e Journées Françaises de Statistique, Avignon, Juin 2017

• P. Gaillard: “Obtaining sparse and fast convergence rates online under Bernstein condition”, CWI-Inria Workshop, September 2017

• P. Gaillard: “Online nonparametric learning”

  • Cambridge Statistics Seminar, October 2017

  • Statistics Seminar of the University Aix-Marseille, December 2017