Provisional program 2023
The plenary room is the DESCARTES room
Sunday, September 17th
18:00 - 21:00 : Welcome and dinner from 19:30 until 21:00 (cold buffet in self-service)
Monday, September 18th
09:15 - 9:30 : Welcome and delivery of badges
9:30 - 10:30 : Contributed session 1: Nonparametric estimation
- Zacharie Naulet. Frontiers to the learning of nonparametric hidden Markov models.
- Janine Steck. Fourier-type density estimation in a tomography problem.
- Mary Savino. A novel approach for estimating functions in the multivariate setting.
10:30 - 11:00 : Break
11:00 - 12:00 : Contributed session 2: Bayesian inference: theory and algorithms
- Samuel Gruffaz. On the convergence of the HMC algorithm and NUTS sampler.
- Paul Rosa. Manifold adaptive regression.
- Kylliann De Santiago. Mixture of Stochastic Block Models for multiview clustering.
12:00 : Lunch
15:30 - 17:30 : Gareth Roberts Lecture 1
17:30 - 18:00 : Break
18:00 - 19:00 : Contributed session 3: Statistical methods for genomics and ecology
- Maud Delattre. Bayesian high-dimensional covariate selection in non-linear mixed-effects models.
- Charlotte Baey. Calibration of a bumble bee foraging model using ABC.
- Emre Anakok. Bipartite and fair graph variational auto-encoder.
19:30 : Friendly aperitif
20:00 : Dinner
Tuesday, September 19th
09:00 - 11:00 : Gareth Roberts Lecture 2
11:00 - 11:30 : Break
11:30 - 12:30 : Contributed session 4: Finite sample inference
- Felix Kuchelmeister. Finite sample rates for logistic regression with small noise or few samples.
- Hugo Chardon. Finite sample analysis of the maximum likelihood estimator in logistic regression.
- Margaux Zaffran. Conformal prediction with missing values.
12:30 : Lunch
15:30 - 17:30 : Marco Cuturi Lecture 1
17:30 - 18:00 : Break
18:00 - 18:15 : Flash talks (2 minutes per speaker)
- Sixiao Zhu. Kernel change point detection and its bandwidth calibration issues.
- Tom Guédon. Bootstrap test for variance components in nonlinear mixed effects models.
- Pierre Marion. Convergence and generalization of neural networks in the large-depth limit.
- Ibrahim Kaddouri. Clustering observations of nonparametric hidden Markov models.
- Maximilian Graf. Permutation estimation for crowdsourcing.
- Samy Clementz. Stopping rules for projection-based learning algorithm.
- Ricardo Blum. Consistency in regression models with interaction using variant of random forest.
- Taher Jalal. Nonparametric density estimation for the small jumps of Lévy processes.
18:15 - 19:15 : Poster Discussion
19:30 : Provencal Dinner
Wednesday, September 20th
09:00 - 10:30 : Gareth Roberts Lecture 3
10:30 - 11:00 : Break
11:00 - 13:00 : Marco Cuturi Lecture 2
13:00 : Lunch
14:30 - 19:30 : Free time / Activities
19:30 : Dinner
Thursday, September 21st
09:00 - 10:30 : Marco Cuturi Lecture 3
10:30 - 11:00 : Break
11:00 - 12:30 : Gareth Roberts Lecture 4
12:30 : Lunch
16:00 - 17:30 : Marco Cuturi Lecture 4
17:30 - 18:00 : Break
18:00 - 19:00 : Contributed session 5: Optimisation and learning
- Laura Hucker. Early stopping for conjugate gradients in statistical inverse problems.
- Clément Lezane. Optimal algorithms for stochastic complementary composite minimization.
- Yannis Bekri. On robust counterpart of linear inverse problems.
19:30 : Dinner
Friday, September 22nd
08:30 - 10:00 : Gareth Roberts Lecture 5
10:00 - 10:30 : Break
10:30 - 12:00 : Marco Cuturi Lecture 5
12:00 : Lunch and leaving