Lecture

Kernel Methods: Neural Networks

In course

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Description

This lecture covers the fundamentals of neural networks, focusing on radial basis function (RBF) kernels, drawbacks of local methods, the curse of dimensionality, two-layer neural networks, activation functions, kernel ridge regression, support vector machines (SVM), and non-linear projections.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_advve6y2

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Ontological neighbourhood

Information engineering

Machine learning: Artificial neural networks, Topics in machine learning, Decision tree learning

Mathematics

Analysis: Numerical analysis

Geometry: Euclidean geometry

Statistics

Data analysis: Regression analysis

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