Lecture

Artificial Neural Networks and Deep Learning: Loss landscape and optimization methods

In course

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Description

This lecture covers the error function landscape, minima, saddle points, momentum, ADAM optimizer, and the No Free Lunch Theorem in the context of artificial neural networks. It also discusses the differences between shallow and deep networks, the task of hidden neurons, and gradient descent optimization methods.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_jwiqqhq9

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Ontological neighbourhood

Information engineering

Machine learning: Artificial neural networks

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