Lectures related to Convex Optimization: Convex Functions

Stochastic Gradient Descent Log in to Mediaspace to watch this video

Explores stochastic gradient descent optimization and the Mean-Field Method in neural networks.

Sylvester's Theorem: Orthogonal Bases Log in to Mediaspace to watch this video

Explores Sylvester's Theorem and the importance of orthogonal bases in linear algebra.

Orthogonal Bases in Vector Spaces Log in to Mediaspace to watch this video

Covers orthogonal bases, Gram-Schmidt method, linear independence, and orthonormal matrices in vector spaces.

Untitled Log in to Mediaspace to watch this video

Vector Spaces: Definitions and Examples Log in to Mediaspace to watch this video

Covers the definition and examples of vector spaces, including subspaces and linear transformations.

Convex Optimization: Examples of Convex Functions Log in to Mediaspace to watch this video

Explores convex optimization, convex functions, and their properties, including strict convexity and strong convexity, as well as different types of convex functions like linear affine functions and norms.