Lecture

Max Entropy and Monte Carlo

Description

This lecture covers the principles of max entropy, focusing on the distribution of probability to maximize entropy and variance. It also delves into the concept of Shannon's entropy and the application of Lagrange multipliers. The lecture further explores Monte Carlo sampling techniques for estimation and discusses the curse of dimensionality in machine learning.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_kjaj3m4c

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

Data collection: Statistical sampling

Data analysis: Survival analysis

Mathematics

Geometry: Euclidean geometry

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