Archives
10 évènements found.
Mis en avant
CRYPTO: Antonio Flórez-Gutiérrez – Design and Analysis of ZIP-AES
Bâtiment Fermat, salle 4205Based on "General Practical Cryptanalysis of the Sum of Round-Reduced Block Ciphers and ZIP-AES": Antonio Flórez-Gutiérrez, Lorenzo Grassi, Gregor Leander, Ferdinand Sybleyras and Yosuke Todo, presented at ASIACRYPT 2024. In recent years, there has been an increased interest in the
Mis en avant
Séminaire des jeunes
Bâtiment Fermat, salle 4205Pierre-Guy Plamondon: The category of Cohen-Macaulay modules over the algebra A of [JKS]
Bâtiment Fermat, salle 4205First of a series of lectures on Bernt Tore Jensen, Alastair King, Xiuping Su, A categorification of Grassmannian cluster algebras, arXiv:1309.7301
EDP : Annabelle Collin (Université de Nantes) : Sequential Data Assimilation for Oncology: Theory & Practice illustrations.
Bâtiment Fermat, salle 4205Abstract: The development of PDE models capable of describing tumor growth may help to monitor disease progression or predict the efficacy of different therapeutic strategies. However, to be truly informative or predictive, these models need to be corrected and/or parameterized
EDP : Simão Correia (Instituto Superior Técnico, Lisbonne) : Blow-up stability of self-similar solutions to the modified Korteweg-de Vries equation
Bâtiment Fermat, salle 4205Abstract : Self-similar solutions for the modified Korteweg-de Vries equation are of both physical and mathematical interest. On the physical side, among several applications, they model the formation of sharp corners in planar vortex patches. Mathematically, they describe the asymptotic
PS : Benjamin Dupuis (INRIA et ENS Paris) : Data-dependent Uniform Generalization Bounds
Bâtiment Fermat, salle 4205We study data-dependent uniform generalization bounds by approaching the problem from a PAC-Bayesian perspective. We first apply the PAC-Bayesian framework on ``random sets'' in a rigorous way, where the training algorithm is assumed to output a data-dependent hypothesis set after
PS : Umut Simsekli (INRIA et ENS Paris) : Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD
Bâtiment Fermat, salle 4205Neural network compression has been an increasingly important subject, not only due to its practical relevance, but also due to its theoretical implications, as there is an explicit connection between compressibility and generalization error. In this talk, I will present