Statistics/Learning at Paris-Saclay

vendredi 8 janv. 2016, 09:00 → 18:30 Europe/Paris

Centre de Conférences Marilyn et James Simons (Le Bois-Marie)

The aim of this workshop is to bring together mathematicians and computer scientists around some talks on recent results in statistics and machine learning. Various topics will be presented, among which sequential learning, aggregation of estimators, Hidden Markov models, network inference and optimization for machine learning.

Organised by : Sylvain ARLOT

Invited speakers :

Pierre Alquier (ENSAE)
Stéphane Gaiffas (Ecole Polytechnique)
Claire Lacour (Université Paris-Sud)
Odalric-Ambrym Maillard (INRIA - Université Paris-Sud)
Yann Ollivier (CNRS - Université Paris-Sud)
Joseph Salmon (LTCI, CNRS, Télécom ParisTech)

 

 

Abstracts abstracts.pdf

Poster poster_arlot.pdf

PowerPoint Alquier alquier.pdf

PowerPoint Gaiffas gaiffas.pdf

PowerPoint Lacour lacour.pdf

PowerPoint Maillard maillard.pdf

PowerPoint Salmon salmon.pdf

09:00 → 18:30 Journée Statistique: Apprentissage Paris-Saclay¶

09:00 Café d'accueil

10:00 Pierre Alquier¶

PAC-Bayesian bounds for aggregation of estimators: introduction and computational issues

Transparents alquier.pdf

10:50 Pause Café

11:20 Joseph Salmon¶

GAP safe screening rule for sparsity enforcing penalties

Transparents salmon.pdf

12:10 Odalric-Ambrym Maillard¶

Multi-armed bandits: Proof techniques and challenges

Transparents maillard.pdf

13:00 Déjeuner

14:30 Claire Lacour¶

Minimax adaptive estimation of nonparametric hidden Markov models

Transparents lacour.pdf

15:20 Stéphane Gaiffas¶

Concentration for matrix martingales and microscopic activity of social networks using Hawkes processes

Transparents gaiffas.pdf

16:10 Pause café

16:40 Yann Ollivier¶

Learn as you go: Training recurrent neural networks and dynamical systems

17:30 Discussion