To Describe or Construct Statistical Learning Models Using the Category-theoretical Language

To Describe or Construct Statistical Learning Models Using the Category-theoretical Language

Statistical learning is a fascinating field that has long been the mainstream of machine learning/artificial intelligence. A large number of results have been produced which can be widely applied to real-world problems.

Machine Learning Experts - Sasha Luccioni

Linear and Quadratic Discriminant Analysis: Tutorial

arXiv:1906.02590v2 Announce Type: replace-cross Abstract: This tutorial explains Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) as two fundamental classification methods...

Generalized Distribution-Free Semi-Supervised Learning with Risk Rewrite

arXiv:2607. 11947v1 Announce Type: cross Abstract: Typical semi-supervised learning (SSL) methods rely on distributional assumptions, and their performance degrades when these are violated.

Information-Theoretic Foundations for Machine Learning

arXiv:2407. 12288v5 Announce Type: replace-cross Abstract: The progress of machine learning over the past decade is undeniable.

Fitting and Learning Basis-Restricted Propositional Formulas

arXiv:2609.08961v1 Announce Type: cross Abstract: For a finite set $O$ of Boolean functions, we consider the class of propositional formulas built using the functions in $O$ as connectives. We determ...