This course provides foundational and advanced concepts in statistical learning theory, essential for analyzing complex data and making informed predictions. Students will delve into both asymptotic ...

A topic in the theory of statistics, such as probability theory, Bayesian statistical theory, statistical decision theory, martingales and stochastic integrals. The fourth number of the course code ...

Catalog description: Presents the underlying theory behind machine learning in proofs-based format. Answers fundamental questions about what learning means and what can be learned via formal models of ...

We estimate real-world private firm default probabilities over a fixed time horizon. The default probabilities are conditioned on a vector of explanatory variables which include financial ratios, ...

How does an individual neuron learn? originally appeared on Quora: the knowledge sharing network where compelling questions are answered by people with unique insights. Answer by Paul King, ...

Modern statistical methodologies are increasingly focused on addressing the challenges associated with high-dimensional data through advanced techniques for variable selection and model estimation.

Successful completion of 50% of the homework sets as well as a written exam at the end of the course (format, date and time t.b.a.) ...