Distributed Algorithms for Networked Control Systems

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Explores statistical models, parameter estimation, and sampling distributions in probability and statistics.

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Explores statistical inference for bandit data, focusing on personalized treatment actions and challenges of standard estimators.

Explores the IRLS algorithm for weighted least squares estimation in GLM.

Covers linear regression, regularization, and probabilistic models in generating labels.

Explains the concept of least squares solutions and their application in finding the closest solution to a system of equations.

Covers the concept of least square estimation and its real-world applications.

Explores linear least squares, normal equations, and the importance of linear regression in minimizing errors.