Linear Dimensionality ReductionExplores linear dimensionality reduction through PCA, variance maximization, and real-world applications like medical data analysis.
Oja's RuleCovers Oja's rule in Neurorobotics, focusing on learning eigenvectors and eigenvalues for capturing maximal variance.
Dependence in Random VectorsExplores dependence in random vectors, covering joint density, conditional independence, covariance, and moment generating functions.