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This series of lectures aims at describing the main notions involved in the mathematical analysis of Statistical Learning problems.

Here is the outline of the topics we plan to cover:

  1. Introduction: What is Statistical learning about?
  2. Concentration of Sub-Gaussian Random variables
  3. Concentration of Sub-Exponential RVs and Bernstein's inequality
  4. The Empirical Risk Minimization principle
  5. Complexity measures
  6. Davis-Kahan theorem: PCA and Spiked covariance model
Chemin ROF:
/Mathématiques et informatique/M2 Ind Modélisation et Méthodes Math. en Economie et Finance/Semestre 3/UE 1 "Cours fondamentaux"/Choix 20 ECTS/Choix 2X5 + 4X2.5 ECTS/Choix 4x2.5 ECTS/Statistical learning
Chemin ROFid:
/27/UP1-PROG-27-MIX501-125/UP1-PROG-ELP-X5I1S325/UP1-C-ELP-X5AI1125/UP1-C-ELP-X5I15A25/UP1-C-ELP-X5I15E25/UP1-C-ELP-X5I15J25/UP1-C-ELP-X5I13719
Code Apogée: X5I13719
Composante: Mathématiques et informatique
Semestre: 3
Niveau: M2
Niveau LMDA: Masters
Niveau année: 5
Composition: Cours magistral
Diplôme: M2 Ind Modélisation et Méthodes Math. en Economie et Finance
Domaine ROF: [Mathématiques appliquées - sciences soci] Mathématiques appliquées - sciences soci
Type ROF: [M2]
Nature ROF: [5] BAC+5
Cycle ROF: [2]
Rythme ROF: [Initiale,Init. Ech.]
Langue: []
Mention: Mathématiques et applications
Spécialité: Modélisation et Méthodes Mathématiques en Economie et Finance
Approbateur proposé Id: 291260
Approbateur effectif Id: 291260
Date validation: Wednesday, 17 September 2025, 9:06 AM
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