Related lectures (208)
Optimality in Decision Theory: Unbiased Estimation
Explores optimality in decision theory and unbiased estimation, emphasizing sufficiency, completeness, and lower bounds for risk.
Generalization Error
Discusses mutual information, data processing inequality, and properties related to leakage in discrete systems.
Parameter Estimation: Detection & Estimation
Covers the concepts of parameter estimation, including unbiased estimators and Fisher information.
Binary Spiked Matrix Estimation
Explores binary spiked matrix estimation, analyzing consistent equations and Bayesian estimators.
Probabilistic Estimation in Spin Glass Card Game
Explores probabilistic estimation in the Spin Glass Card game, emphasizing room splitting based on a given parameter.
Maximum Likelihood Estimation: Properties and Applications
Explores the properties and challenges of Maximum Likelihood Estimators.
Statistical Models and Parameter Estimation
Explores statistical models, parameter estimation, and sampling distributions in probability and statistics.
Gradient Descent
Covers the concept of gradient descent, a universal algorithm used to find the minimum of a function.
Distribution Estimation
Explores distribution estimation, constraints in estimators, and competitive analysis for robust estimation.
Statistical Estimators
Explains statistical estimators for random variables and Gaussian distributions, focusing on error functions for integration.

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