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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

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1

A Literature Study Concerning Generalization Error Bounds for Neural Networks via Rademacher Complexity

Nordenfors, Oskar January 2021 (has links)
In this essay some fundamental results from the theory of machine learning and neural networks are presented, with the goal of finally discussing bounds on the generalization error of neural networks, via Rademacher complexity. / I denna uppsats presenteras några grundläggande resultat från teorin kring maskininlärning och neurala nätverk, med målet att slutligen diskutera övre begräsningar på generaliseringsfelet hos neurala nätverk, via Rademachers komplexitet.
machine
learning
neural
networks
generalization
error
rademacher
complexity
maskininlärning
neurala
nätverk
generaliseringfel
rademachers
komplexitet
Mathematics
Matematik
Probability Theory and Statistics
Sannolikhetsteori och statistik

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