In computer science, computational learning theory (or just learning theory) is a subfield of artificial intelligence devoted to studying the design and analysis of machine learning algorithms.

Our goal in this chapter is to gradually build up the probably approximately correct (PAC) learning framework while emphasising the key components of the learning model.

Computational learning theory is a branch of theoretical computer science that formally studies how to design computer programs capable of learning and identifies the computational limits of …

Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying …

Sep 7, 2020 · Computational learning theory may be thought of as an extension or sibling of statistical learning theory, or SLT for short, that uses formal methods to quantify learning …

This is the second lecture of computational learning theory, where we move toward formalizing our model by introducing key examples of algorithms that will motivate PAC learnability.

Mar 20, 2025 · Computational Learning Theory (CLT) is a branch of machine learning and theoretical computer science that studies the mathematical principles behind learning …

Machine Learning Theory, also known as Computational Learning Theory, aims to understand the fundamental principles of learning as a computational process and combines tools from …

This book shows how artificial intelligence grounded in learning theories can promote individual learning, team productivity and multidisciplinary knowledge-building.

Apr 11, 2024 · Computational Learning Theory (CLT) stands as a cornerstone in the realm of artificial intelligence (AI), providing a mathematical foundation for understanding how …