Oja's RuleCovers Oja's rule in Neurorobotics, focusing on learning eigenvectors and eigenvalues for capturing maximal variance.
Linear Dimensionality ReductionExplores linear dimensionality reduction through PCA, variance maximization, and real-world applications like medical data analysis.
Market Response FunctionsExplores market response functions, flash crashes, correlation estimation, and noise filtering in finance.
Multivariate Methods IExplores multivariate methods like PCA, SVD, PLS, and ICA for dimensionality reduction in functional brain imaging.
