Lecture

Regression Reloaded: Synthetic Dataset Construction and Parameter Estimation

In course

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Description

This lecture covers the construction of a synthetic dataset for linear regression, the estimation of ground truth parameters using least squares, and the verification that the least square solution aligns with the maximum of the log-likelihood. It also explores L2 regularization as a prior for parameter estimation.

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Instructor

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Official source

https://mediaspace.epfl.ch/media/0_uwky8wgj

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis, Cross-validation

Statistical inference: Mathematical statistics

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