Lecture

Neural Network: Random Features and Kernel Regression

Description

This lecture covers the concept of random features in neural networks, focusing on regression with non-polynomial features extracted from PDFs. It explains the equivalence between kernel regression and neural network terminology, emphasizing the use of random features to approximate kernel functions.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_dxu81l80

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis

Statistical inference: Non-parametric statistics

Information engineering

Machine learning: Artificial neural networks

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