Lecture

Optimization in Statistics and Machine Learning: Maximum Likelihood Estimation

In course

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Description

This lecture covers maximum likelihood estimation for parametric distribution estimation, linear measurement models, logistic regression for heart attack prediction, and covariance estimation for Gaussian variables. It also discusses support vector machines for classification problems, including hard and soft margin SVMs. The instructor explains the log-likelihood function, empirical logloss minimization, and the dual and primal quadratic programming formulations for SVMs.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_yg2xy18u

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

Data analysis: Regression analysis

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