A tutorial introduction to the minimum description length principle

2004-06-04 · Peter Grunwald

This tutorial provides an overview of and introduction to Rissanen's Minimum Description Length (MDL) Principle. The first chapter provides a conceptual, entirely non-technical introduction to the subject. It serves as a basis for the technical introduction given in the second chapter, in which all the ideas of the first chapter are made mathematically precise. The main ideas are discussed in great conceptual and technical detail. This tutorial is an extended version of the first two chapters of the collection "Advances in Minimum Description Length: Theory and Application" (edited by P.Grunwald, I.J. Myung and M. Pitt, to be published by the MIT Press, Spring 2005).

📄 PDF Abstract BibTeX arXiv:math/0406077

Code (1)

thlarsen13/thlarsen_uncertainty_models tf

Minimum Description Length Revisited

2019-08-21 · Peter Grünwald, Teemu Roos

This is an up-to-date introduction to and overview of the Minimum Description Length (MDL) Principle, a theory of inductive inference that can be applied to general problems in statistics, machine learning and pattern re…

Data Compression Model Selection Two-sample testing

The Minimum Description Length Principle for Pattern Mining: A Survey

2020-07-28 · Esther Galbrun

This is about the Minimum Description Length (MDL) principle applied to pattern mining. The length of this description is kept to the minimum. Mining patterns is a core task in data analysis and, beyond issues of efficie…

Model Selection Survey

Extending Universal Intelligence Models with Formal Notion of Representation

2013-06-06 · Alexey Potapov, Sergey Rodionov

Solomonoff induction is known to be universal, but incomputable. Its approximations, namely, the Minimum Description (or Message) Length (MDL) principles, are adopted in practice in the efficient, but non-universal form.…

Model Optimization

Inferring Latent dimension of Linear Dynamical System with Minimum Description Length

2019-06-23 · Yang Li

Time-invariant linear dynamical system arises in many real-world applications,and its usefulness is widely acknowledged. A practical limitation with this model is that its latent dimension that has a large impact on the …

Model Selection

Minimum Description Length Skills for Accelerated Reinforcement Learning

2021-03-09 · ICLR Workshop SSL-RL 2021 5 · Jesse Zhang, Karl Pertsch, Jiefan Yang, Joseph J Lim

Humans can quickly learn new tasks by reusing a large number of previously acquired skills. How can we discover such reusable skills for artificial agents when given a large dataset of prior experience? Past works levera…

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)