Explores maximum likelihood estimation in linear models, covering Gaussian noise, covariance estimation, and support vector machines for classification problems.
Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.
Explores phase transitions in signal processing, demonstrating their impact on signal reconstruction and the application of threshold algorithms in image denoising.