Vazirani & Kearns. An Introduction to Computational Learning Theory
Emphasizing issues of computational efficiency, It introduces a number of central topics in computational learning theory.
- from
- Theoretical Computer Science
- added
- 2026-10-10
- likes
- 0
similar
-
-
Livni. COS 511 Theoretical Machine Learning. Princeton cs.princeton.edu
Formally define and study various models that have been proposed for learning. The course will present and contrast the statistical, computational and online models for learning. We will present and rigorously analyze some of the most successful algorithms in machine learning…
-
Moitra. Theoretical Foundations for Deep Learning. MIT people.csail.mit.edu
It explores theoretical foundations for deep learning, emphasizing the following themes: (1) Approximation: What sorts of functions can be represented by deep networks, and does depth provably increase the expressive power? (2) Optimization: Essentially all optimization…
-
-
Blum. An Introduction to the Theory of Machine Learning. TTIC home.ttic.edu
The basic theory underlying machine learning and the process of generalizing from data.
-
Shalev-Shwartz. Understanding Machine Learning: From Theory to Algorithms cambridge.org
It provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms.
Theoretical Computer Science › Books: “Emphasizing issues of computational efficiency, It introduces a number of central topics in computational learning theory.”