Lecture

Generalized Linear Models

In course

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Description

This lecture covers the concept of Generalized Linear Models, including the assumptions, statistical properties, and practical applications. It delves into various topics such as high-dimensional statistics, Bayesian methods, compressed sensing, and perception. The instructor discusses the challenges of working with noisy data and the importance of understanding the linearized models in different contexts.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_2tuhkqee

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis

Information engineering

Signal processing: Digital image processing

Mechanical engineering

Acoustical engineering: Architectural acoustics

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