Program 2022
StatMathAppli 2022 - Sunday 28 August to Friday 2 September - La Villa Clythia, Fréjus
The plenary room is the DESCARTES room
Sunday 28 August
18:00 - 22:00 : Welcome and dinner from 19:30 until 21:00 (cold buffet in self-service)
Monday 29 August
08:45 - 9:00 : Welcome and delivery of badges
9:00 - 11:00 : Lecture 1 by Richard Nickl
11:00 - 11:30 : Break
11:30 - 12:30 : Contributed talks, session 1: Bayesian inference and generative models
Geerten Koers: Bayesian linear methods for non-linear inverse problems.
Clément Berenfeld: Bayesian density estimation near unknown manifolds.
Jakiw Pidstrihgach: Score-based generative models detect manifolds.
12:30 : Lunch
15:30 - 17:30 : Lecture 2 by Rebecca Willett
17:30 - 18:00 : Break
18:00 - 19:00 : Contributed talks, session 2: Machine learning and optimisation
Julian Tachella: Equivariant imaging: learning to solve imaging inverse problems without ground-truth.
Constantin Philippenko: Preserved central model for faster bidirectional compression in distributed settings.
Vincent Divol: Estimation of optimal transport maps in high-dimension.
19:30 : Friendly aperitif
20:00 : Dinner
Tuesday 30 August
09:00 - 11:00 : Lecture 3 by Richard Nickl
11:00 - 11:30 : Break
11:30 - 12:30 : Contributed talks, session 3: Network inference and clustering
Emre Anakok: Accounting for the observational process when unraveling the structure of the interaction network.
Camille Champion: Microbial network inferences and clustering.
Deborah Sulem: Regularized spectral methods for clustering signed networks.
12:30 : Lunch
15:30 - 16:00 : Flash talks (2 minutes per speaker)
16:00 - 17:00 : Poster Discussion
Bernhard Stankewitz: Sequential early stopping for L2-boosting in high-dimensional linear models.
Guillaume Maillard: Robust estimation in total variation distance under a shape constraint.
Maté Kormos: Caliper matching estimator of average treatment effects.
Olympio Hacquard: Classification of measures, application to persistence diagrams.
Jean-Baptiste Fermanian: Stein’s phenomenon for the multi-task averaging problem in high-dimension.
Eddy Ella Minsta: Classification procedure for diffusion paths.
Linus Bleistein: Theoretical Guarantees for learning with signatures.
Maia Tienstra: Frequentist Ensemble Kalman filter.
Diksha Bhandari: Neural network modelling of brain responses during language comprehension.
17:00 - 17:30 : Break
17:30 - 19:00 : Lecture 4 by Rebecca Willett
19:30 : Provencal Dinner
Wednesday 31 August
09:00 - 10:30 : Lecture 5 by Richard Nickl
10:30 - 11:00 : Break
11:00 - 12:30 : Lecture 6 by Rebecca Willett
12:30 : Lunch
14:30 - 19:30 : Free time / Activities
19:30 : Dinner
Thursday 1 September
09:00 - 11:00 : Lecture 7 by Richard Nickl
11:00 - 11:30 : Break
11:30 - 12:30 : Contributed talks, session 4: Adaptive inference and testing
Perrine Lacroix: Penalty functions calibration for high-dimensional Gaussian linear regression.
Tom Guédon: Variance components testing in mixed effects models in small sample size.
Neil Deo: On Adaptive confidence sets for the Wasserstein distances.
12:30 : Lunch
16:00 - 17:30 : Lecture 8 by Rebecca Willett
17:30 - 18:00 : Break
18:00 - 19:00 : Contributed talks, session 5: Bandit problems
Dorian Baudry: Optimal Thompson Sampling strategies for support-aware CVaR bandits.
Marc Jourdan: Top two algorithms revisited.
El Mehdi Saad: Constant regret for sequence prediction with limited advice.
19:30 : Dinner
Friday 2 September
09:00 - 10:30 : Lecture 9 by Rebecca Willett
10:30 - 11:00 : Break
11:00 - 12:00 : Contributed talks, session 6: Temporal data analysis
Grégoire Szymanski: Optimal estimation of the rough Hurst parameter.
Liudmila Pishchagina: Multiple change-point detection problem for bi-variate time-series.
Alexandre Lecestre: Robust estimation in finite state space hidden Markov models.
12:00 : Lunch and leaving