Detection & EstimationCovers the fundamentals of detection and estimation theory, focusing on mean-squared error and hypothesis testing.
Linear MM SE EstimationCovers the principles of linear MM SE estimation and the minimization of errors in linear regression.
Sub Exponential BoundsExplores sub exponential bounds and Bernstein conditions in verifying sub exponentiality.
Generalization BoundExplores the relationship between empirical risk minimization and generalization error in machine learning.
Exponential FamilyCovers the properties of the exponential family and the estimation of parameters.
Exponential FamilyExplores the Exponential Family distribution, covering entropy, energy, and moments.
Exponential FamilyCovers the concept of the exponential family and discusses forward and backward maps, expensive computations, parameters, functions, and convexity.
CompressionCovers the concept of compression and constructing prefix-free codes based on given information.
