Expectation Value and Convex Functions

Related lectures (28)

Page 1 of 3

Explores the Rockafellar Theorem in optimal transport, focusing on c-cyclical monotonicity and convex functions.

Introduces the key concepts of convexity and its applications in different fields.

Explores subgradients in convex functions, emphasizing non-differentiable yet convex scenarios and properties of subdifferentials.

Explores convex functions, global minima, and their relationship with differentiability.

Covers the concept of convex functions and their applications in optimization problems.

Introduces convex sets and functions, discussing minimizers, optimality conditions, and characterizations, along with examples and key inequalities.

Explores geodesic convexity in metric spaces and its applications, discussing properties and the stability of inequalities.

Explores elementary results in convex optimization, including affine, convex, and conic hulls, proper cones, and convex functions.

Covers basic properties of conditional expectation and Jensen's inequality in probability theory.

Covers optimization techniques in machine learning, focusing on convexity and its implications for efficient problem-solving.