The ability to learn about regularities in the environment and to make predictions about future events is fundamental for adaptive behaviour. We have previously shown that people can implicitly encode ...

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 ...

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 ...

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 ...

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, ...

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, ...