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Related lectures (32)

Observers References

Explores the addition of a reference input to controllers and the design of autonomous and tracking-error estimators.

Empirical Estimation: Distribution Estimation

Covers methods to estimate probability distributions from samples.

Proof for Rademacher Control

Presents a proof for Rademacher control of the expected estimation error, focusing on empirical process control.

Model Selection: AIC and BIC

Explores model selection using AIC and BIC criteria, addressing different questions and the importance of sparsity in selecting the best model.

The Stein Phenomenon and Superefficiency Log in to Mediaspace to watch this video

Explores the Stein Phenomenon, showcasing the benefits of bias in high-dimensional statistics and the superiority of the James-Stein Estimator over the Maximum Likelihood Estimator.

Spin Glasses and Bayesian Estimation Log in to Mediaspace to watch this video

Covers the concepts of spin glasses and Bayesian estimation, focusing on observing and inferring information from a system closely.

Bayes Estimator, Simulated Annealing and EM Log in to Mediaspace to watch this video

Covers Bayes estimator, Simulated Annealing, and EM for parameter estimation.

Statistical Theory: Decision Theory Framework Log in to Mediaspace to watch this video

Explores the Decision Theory Framework in Statistical Theory, viewing statistics as a random game with key concepts like admissibility, minimax rules, and Bayes rules.

Bayes Estimator: Definition and Application Log in to Mediaspace to watch this video

Introduces the Bayes estimator, explaining its definition, application in quadratic cost scenarios, and importance in probabilistic reasoning.

Bayesian Decision Theory: Utility, Risk, and Classification Log in to Mediaspace to watch this video

Covers Bayesian decision theory, cost functions, classification, and decision rules.

Dynamic Model Simulation: EPFL Racing Team Log in to Mediaspace to watch this video

Introduces a project to build a dynamic model for simulating racing car performance.

Biased Monte Carlo Markov Chain Log in to Mediaspace to watch this video

Explores Biased Monte Carlo Markov Chain, including Bayes-optimal estimation and Metropolis-Hastings algorithm.

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