Martingales: More Theory

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Related lectures (30)

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Poisson Paradigm: Qualitative / Quantitative

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

Probability Theory: Markov's Theorem

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

Interlacing Polynomials

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

Probability and Statistics

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

Martingales and Conditional Expectations

Explores Brun's Sieve, Martingales, and Conditional Expectations in probability theory.

Dependence and Correlation

Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.

Pseudorandomness: Theory and Applications

Explores pseudorandomness theory, AI challenges, pseudo-random graphs, random walks, and matrix properties.

Conditional Probability: Prediction Decomposition

Explores conditional probability, Bayes' theorem, and prediction decomposition for informed decision-making.

Conditional Density and Expectation

Explores conditional density, expectations, and independence of random variables with practical examples.

Probability and Statistics: Fundamentals

Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.