Lectures related to Conical combination

Covers Principal Component Analysis for yield curve shape estimation and dimension reduction in interest rate models.

Covers unsupervised learning with PCA and K-means for dimensionality reduction and data clustering.

Explores the complexity of convex hulls and the concept of vertices within them.

Covers the definition and properties of determinants for square matrices, including elementary operations and Lagrange's theorem.

Introduces convex functions, covering affine, convex, and conic hulls, transformations, inequalities, and conditions for convexity.

Explores linear dependence of vectors, demonstrating examples and conditions for collinearity.

Explores algebraic operations on limits of sequences and discusses the uniqueness of limits and properties of convergent and divergent sequences.