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Bayesian Nonparametric Statistics École d’Été de Probabilités de Saint-Flour LI - 2023 /

This up-to-date overview of Bayesian nonparametric statistics provides both an introduction to the field and coverage of recent research topics, including deep neural networks, high-dimensional models and multiple testing, Bernstein-von Mises theorems and variational Bayes approximations, many of wh...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Egile nagusia: Castillo, Ismaël (Egilea)
Erakunde egilea: SpringerLink (Online service)
Formatua: Baliabide elektronikoa eBook
Hizkuntza:ingelesa
Argitaratua: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Edizioa:1st ed. 2024.
Saila:École d'Été de Probabilités de Saint-Flour ; 2358
Gaiak:
Statistics .
Machine learning.
Mathematical optimization.
Calculus of variations.
Statistical Physics.
Probabilities.
Statistical Theory and Methods.
Machine Learning.
Calculus of Variations and Optimization.
Probability Theory.
Sarrera elektronikoa:https://doi.org/10.1007/978-3-031-74035-0
Etiketak: Etiketa erantsi
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!
Aurkibidea:
  • -1. Introduction, rates I.-2. Rates II and first examples.-3. Adaptation I: smoothness.-4. Adaptation II: high-dimensions and deep neural networks
  • 5. Bernstein-von Mises I: functionals
  • 6. Bernstein-von Mises II: multiscale and applications
  • 7. classification and multiple testing
  • 8. Variational approximations.

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