Chernoff bound

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Related lectures (32)

Page 3 of 4

Quantization of Probability Distributions

Covers quantization of probability distributions, statistical k-means clustering, mean estimation, robust clustering methods, and open research questions.

Exact Methods for Integer Optimization

Covers exact methods for integer optimization, emphasizing Branch and Bound techniques.

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Learning in the Presence of Distribution Shifts: How does the Geometry of Perturbations Play a Role?

Explores learning challenges with distribution shifts and perturbation geometry, focusing on robust classifiers and natural variation modeling.

Hoeffding's Inequality

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

Markov's Inequality and Hoeffding's Lemma

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

Martingale Inequalities

Explores Hoeffding's and Azuma's inequalities, emphasizing finite difference martingales and exponential bounds.

Applying the learning bound to kernel regression

Discusses the application of the main theorem to least square regression in a RKHS, focusing on LR of the Rademacher bound and Lipschitz constant.

Integer Optimization

Covers optimization problems, minimal packing, and bounds in Integer Optimization.

Real Numbers: Definitions and Bounds

Explains the definitions and properties of maximum, minimum, supremum, and infimum in real numbers.