Lecture

Probabilistic Estimation in Spin Glass Card Game

In course

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Description

This lecture covers the probabilistic estimation techniques used in the Spin Glass Card game, focusing on splitting a room into two groups with similar cards based on a given parameter Y. The instructor explains the Bays-optimal estimator, mean-squared-error, and how to minimize it. The lecture also delves into Monte Carlo Markov Chain algorithms and Metropolis-Hastings Monte Carlo methods. Detailed balance and equilibrium distributions are discussed, along with practical examples and computational strategies.

Instructor

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Official source

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

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Bayesian inference

Data analysis: Regression analysis

Mathematics

Probability theory: Topics in probability theory

Physics

Thermodynamics: Statistical mechanics

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