Évènements / Séminaires

Évènements à venir

Speeding up of kernel-based learning for high-order tensor

Speaker — Ouafae Karmouda (SIGMA team at CRIStAL laboratory, Lille, France) Abstract — Supervised learning is a major task to classify datasets. In our context, we are interested into classification from high-order tensors datasets. The “curse of dimensionality” states that the complexities in terms of storage and computation grow exponentially with the order. As a […]


Séminaire de Alessio Iovine

09/03/2021 – 14h00-15h00 – Online On the utilization of Macroscopic Information for String Stability of a Vehicular Platoon Alessio Iovine (L2S, CentraleSupèlec) Abstract. Interconnected autonomous vehicles have the capability toreduce stop-and-go waves propagation and traffic oscillations via the concept of String Stability. To improve the platoon stability, several cases of information sharing are usually considered […]


Sampling rates for l1 synthesis

Speaker — Claire Boyer (Sorbonne Université) Abstract — This work investigates the problem of signal recovery from undersampled noisy sub-Gaussian measurements under the assumption of a synthesis-based sparsity model. Solving the l1-synthesis basis pursuit allows to simultaneously estimate a coefficient representation as well as the sought-for signal. However, due to linear dependencies within redundant dictionary […]


UQSay #25

The twenty-fifth UQSay seminar on UQ, DACE and related topics, organized by L2S, MSSMAT, LMT and EDF R&D, will take place online on Thursday afternoon, March 4, 2021. 2–3 PM — Victor Picheny (Secondmind) Bayesian optimisation: ablation study, global performance assessment and improvements based on trust regions Bayesian Optimisation algorithms (BO) are global optimisation methods […]


Chance constrained optimization: an overview

Tuesday 2nd March at 11:00 via Microsoft Teams meetingClick here to join the meetingLearn More | Meeting options Speaker: Abdel Lisser, Professor at Paris-Saclay University Title: Chance constrained optimization: an overview Abstract: Chance constrained optimization, also called probabilistic constrained optimization, is one of the main topics in stochastic optimization for dealing with random parameters in optimization problems. A chance […]