Section: Dissemination
Promoting Scientific Activities
Scientific Events Organisation

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

A. d'Aspremont: coorganization of the workshop: “Optimization and Statistical Learning”, Les Houches, France
Member of the Organizing Committees
Journal
Member of the Editorial Boards

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

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.
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 LargeScale and Distributed Optimization, Lund, Sweden, invited talk, June 2017

F. Bach: Summer school on Structured Regularization for HighDimensional 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, minicourse on optimization, September 2017

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

F. Bach: NewYork 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: “Sharpness, Restart and Acceleration”. Foundations of Computational Mathematics, Barcelona.

P. Germain: “Generalization of the PACBayesian Theory, and Applications to SemiSupervised 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: “Obtaining sparse and fast convergence rates online under Bernstein condition”, CWIInria Workshop, September 2017