Notes and Comments on S. Mallat’s Lectures at Collège de France (2019) - Archive ouverte HAL Accéder directement au contenu
Cours Année : 2019

Notes and Comments on S. Mallat’s Lectures at Collège de France (2019)

Résumé

The 2019 course by Stéphane Mallat, Professor at the Collège de France, continues the trend from 2018 by emphasizing 'Why does it work?' This implies that while there are many courses that focus on 'How' to implement various architectures of convolutional neural networks (CNNs), the 'Why' falls within the realm of fundamental research. The course first describes how the ideas of neural networks originated, their different types of applications, and the mathematical questions underlying their success. The demonstration of the Universality theorem of networks with 1 hidden layer is central to the course, as well as its practical inefficiency in the face of the curse of dimensionality. The end of the course covers notions related to optimization.
Fichier principal
Vignette du fichier
Resume-2019_EN.pdf (5.42 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04550718 , version 1 (18-04-2024)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

  • HAL Id : hal-04550718 , version 1

Citer

Jean-Eric Campagne. Notes and Comments on S. Mallat’s Lectures at Collège de France (2019): Deep Neural Networks: how and why. Master. Learning through deep neural networks., https://www.college-de-france.fr/fr/agenda/cours/apprentissage-par-reseaux-de-neurones-profonds, France. 2019, pp.138. ⟨hal-04550718⟩
0 Consultations
1 Téléchargements

Partager

Gmail Facebook X LinkedIn More