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Related lectures (31)

Page 3 of 4

Detection & Estimation

Covers the fundamentals of detection and estimation theory, focusing on mean-squared error and hypothesis testing.

Partial Derivatives: Composition of Functions

Explores partial derivatives in composing functions, continuity proofs, mean value theorem applications, and integral calculus implications.

Discrete Optimization: Set Covering

Explores the set covering problem through the example of completing a sticker collection at a minimum cost.

Maximal Correlation: Information Measures

Explores maximal correlation in information theory, mutual information properties, Renyi's measures, and mathematical foundations of information theory.

Discrete-Time Markov Chains: Definitions

Covers the definitions and state probabilities of discrete-time Markov chains.

The Backpack Problem

Introduces the backpack problem, a discrete optimization problem with constraints and algorithms to solve it.

Mixture Models: Simulation-based Estimation

Explores mixture models, including discrete and continuous mixtures, and their application in capturing taste heterogeneity in populations.

Constructing Real Numbers: Decimal Expansion

Covers constructing real numbers through decimal expansion and the concept of discrete and continuous random variables.

Discrete Variables: Spatial Arrangement and Neighbourhood

Covers geometric properties, spatial arrangement, autocorrelation, and neighbourhood analysis in geographic information systems.

Discrete Optimization: Traveling Salesman Problem

Covers the traveling salesman problem, modeling, constraints, additional constraints, and network representation.