Big Data: Modeling, Estimation and Selection

from Thursday, 9 June 2016 (11:35) to Friday, 10 June 2016 (17:20)
Ecole Centrale Lille (Grand Amphithéâtre)

        : Sessions
    /     : Talks
        : Breaks
9 Jun 2016
10 Jun 2016
09:00 What can we learn from modelling millions of patient records? A machine learning perspective - Norman Poh (University of Surrey)   (Grand Amphithéâtre)
09:45 Invariance principles for robust learning. An illustration with recurrent neural networks - Yann Ollivier (Paris-Sud University)   (Grand Amphithéâtre)
10:30 --- Pause ---
10:50 High-dimensional data classification with mixtures of sphere-hardening distances - Alejandro Murua (Université de Montréal)   (Grand Amphithéâtre)
11:35 Construction of tight wavelet-like frames on graphs for denoising - Gilles Blanchard (University of Potsdam)   (Grand Amphithéâtre)
13:30 Which analytic methods for Big Data? - Gilbert Saporta (CNAM Paris)   (Grand Amphithéâtre)
14:15 Advances and open questions for neural networks - Jérémie Mary (University of Lille)   (Grand Amphithéâtre)
15:00 Reuse of big data in healthcare: presentation, transformation and analyze of the data extracted from electronic health records - Emmanuel Chazard (Université Lille 2)   (Grand Amphithéâtre)
15:45 --- Pause ---
16:05 Machine Learning approaches for stock management in the retail industry - Manuel Davy (Vékia)   (Grand Amphithéâtre)
16:50 Big Data, myths & opportunities for the consumer finance industry - Khalid Saad-Zaghloul (BNP Paribas) Iuri Paixao (BNP Paribas)   (Grand Amphithéâtre)
18:00 --- Diner ---
14:00 On the Properties of Variational Approximations of Gibbs Posteriors - Pierre Alquier (ENSAE)   (Grand Amphithéâtre)
14:45 Stochastic optimization and high-dimensional sampling: when Moreau inf-convolution meets Langevin diffusion - Eric Moulines (Télécom ParisTech)   (Grand Amphithéâtre)
15:30 --- Pause ---
15:50 Approximate Bayesian inference for large datasets - Nial Friel (Dublin University)   (Grand Amphithéâtre)