Probabilistic Methods in Combinatorics

Related lectures (27)

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Explores Markov's theorem, Chernoff bound, and probability theory fundamentals, including good coloring, 2-colorable graphs, and rare events.

Explores the Poisson Paradigm and dependency measures in ordered pairs and graphs.

Covers girth, independence, probability, union bound, sets, and hypergraph recoloring.

Covers topics related to probability and statistics, including finding specific values and significant events.

Explores interlacing polynomials, real rooted theorems, and pseudo-probabilistic methods in polynomial analysis.

Covers the Poisson Paradigm, including the First/Second Moment Method and Martingales, discussing dependency graphs and Chernoff bounds.

Explores the theory of martingales, including conditional expectations, Chernoff bounds, and Azuma's inequality.

Explores graph coloring, directed cycles, LLL algorithm applications, and element dependencies in graphs.

Explores expanders, Ramanujan graphs, eigenvalues, Laplacian matrices, and spectral properties.

Covers basic probability theory, conditional probability, independence, and Bayes' Theorem.