Compression

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Related lectures (28)

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Entropy and Data Compression: Huffman Coding Techniques

Discusses entropy, data compression, and Huffman coding techniques, emphasizing their applications in optimizing codeword lengths and understanding conditional entropy.

Parameter Estimation

Discusses parameter estimation, including checks, quality, distribution, and statistical properties of estimates.

Distributions & Interpolation Spaces

Covers distributions, interpolation spaces, convergence, and the concept of dual spaces.

Entropy and Algorithms: Applications in Sorting and Weighing

Covers the application of entropy in algorithms, focusing on sorting and decision-making strategies.

Random Variables: Basics and Examples

Explains random variables, distributions, and Bernoulli trials with coin flip examples.

Source Coding Theorems: Entropy and Source Models

Covers source coding theorems, entropy, and various source models in information theory.

Elements of Statistics: Probability and Random Variables

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Sparsest Cut: Bourgain's Theorem

Explores Bourgain's theorem on sparsest cut in graphs, emphasizing semimetrics and cut optimization.

Source Coding Theorem

Explores the Source Coding Theorem, entropy, Huffman coding, and conditioning's impact on entropy reduction.

Basics of Risk Analysis and Management

Introduces the basics of risk analysis and management in civil engineering, covering distributions, statistical reminders, and mathematical interpretation techniques.