Pseudoconvex function

Formal sciences
Theoretical computer science
Algorithms and data structures
Combinatorial optimization

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Related lectures (30)

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Discusses a real function that is increasing and bounded, and its implications on the convergence of a sequence.

Adversarial Machine Learning: Fundamentals and Techniques

Explores adversarial machine learning, covering the generation of adversarial examples, robustness challenges, and techniques like Fast Gradient Sign Method.

Specification of the deterministic part

Explores the Box-Cox transform for modeling non-linear relationships between variables.

Advanced Information Theory: F-Divergences and Generalization Error

Covers f-divergences and generalization error in advanced information theory.

Box-Cox Transform

Explores the Box-Cox transform for investigating nonlinear specifications in models using a parameter lambda.

Gradient Descent Convergence

Explains how gradient descent converges to a function's minimum at a rate of 1 over k.

Convexity and Jacobians

Explores convexity, Jacobians, subdifferentials, and convergence rates in optimization and function analysis.

Optimal Transport: Brenier's Theorem

Discusses Brenier's theorem in optimal transport and the uniqueness of the optimizer.

Isoperimetric Inequality: Optimal Transport

Explores the isoperimetric inequality and its application in optimal transport, discussing properties of optimal maps and quality cases.

Convex Functions

Covers the definition of convex functions and their properties in optimization.