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An Introduction to Information Theory and Entropy (Tom Carter)

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An Introduction to Information Theory and Entropy (Tom Carter)

An Introduction to Information Theory and Entropy (Tom Carter)

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Information Theory in Computer Science

Information Theory in Computer Science

This note explains the following topics: Shearer's Lemma, Entropy, Relative Entropy, Hypothesis testing, total variation distance and Pinsker's lemma, Stability in Shearer's Lemma, Communication Complexity, Set Disjointness, Direct Sum in Communication Complexity and Internal Information Complexity, Data Structure Lower Bounds via Communication Complexity, Algorithmic Lovasz Local Lemma, Parallel Repetition Theorem, Graph Entropy and Sorting.

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Information Theory Lecture Notes

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This is a graduate-level introduction to mathematics of information theory. This note will cover both classical and modern topics, including information entropy, lossless data compression, binary hypothesis testing, channel coding, and lossy data compression.

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