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