Lectures related to Concentration inequality

Explores tail bounds, information bounds, and maximal leakage in the context of generalization error.

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

Explores Talagrand's lemma, Rademacher complexity bounds, and high probability guarantees in learning.

Explores Hoeffding's inequality and the binomial distribution, focusing on error minimization and generalization gaps in predictor selection.

Covers McDiarmid's inequality, providing concentration bounds for functions of independent random variables.

Explores regret in multi-arm bandits, balancing exploration and exploitation for optimal decision-making in real-world applications.

Covers Hoeffding's inequality and concentration inequalities with a focus on sequences of random variables.

Introduces Markov's inequality and Hoeffding's lemma to analyze random variables' behavior.

Covers concentration inequalities and sampling methods for estimating unknown distributions, with a focus on population infection rates.

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

Covers Cramer's theorem and Hoeffding's inequality in the context of the large deviations principle.

Delves into powers and roots, emphasizing irrational equations and the disjunction of cases.

Covers the Law of Large Numbers, Central Limit Theorem, Chernoff bounds, and PAC bounds in probability theory.

Explores the convergence of martingales under specific conditions and previews upcoming topics on martingale theorems and inequalities.

Explores two lower bounds for the analytical Traveling Salesman Problem, focusing on H(K) and H'(r) functions.

Explains Chernoff bounds, extractors, and their theorems with proofs.

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

Explores Hoeffding's inequality and its applications in probability theory and statistical analysis.

Covers test statistics, threshold values, and lower bounds for estimating properties.