Minimum Description Length on the Web - a new www site

[Henry Tirri]

I am pleased to announce a recently created web-resource for Minimum 
Description Length  (MDL) research at

http://www.mdl-research.org/

The site is maintained by the Complex Systems Computation Group (CoSCo) 
at the Helsinki Institute for Information Technology.

We will be gradually building the resource to be more comprehensive, and all
feedback and comments are appreciated.

Henry Tirri


Brief description of the site:
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What is MDL?

The purpose of statistical modeling is to discover regularities in 
observed data. The success in finding such regularities can be measured 
by the length with which the data can be described. This is the 
rationale behind the Minimum Description Length (MDL) Principle 
introduced by Jorma Rissanen (Rissanen, 1978).

"The MDL Principle is a relatively recent method for inductive 
inference. The fundamental idea behind the MDL Principle is that any 
regularity in a given set of data can be used to compress the data, i.e. 
to describe it using fewer symbols than needed to describe the data 
literally." (Grnwald, 1998)

What is mdl-research.org?

Minimum Description Length on the Web is intended as a source of 
information for everyone who wants to know more about MDL. The site 
contains links and references to suggested reading, tutorials, lecture 
notes, etc. on MDL as well as links to people who are working on MDL and 
related topics.

The Reading section contains references to selected articles, books, and 
lecture material, and links to journals and conferences that publish MDL 
related material.

The Demonstrations section will illustrate MDL through on-line 
demonstrations. The section is under construction but you can already 
find a demonstration on Markov chain order selection.

The People section has links to researchers who are working on MDL and 
related fields. You can find loads of related material in their homepages.

The Related Topics section is a short collection of links to MDL related 
topics, such as information theory, Bayesian statistics, etc. It can 
help you locate useful background knowledge.

References:

J.Rissanen, Modeling by shortest data description. Automatica, vol. 14 
(1978), pp. 465-471.

Peter Grnwald, The Minimum Description Length Principle and Reasoning 
under Uncertainty, Ph.D. Thesis, ILLC Dissertation Series DS 1998-03, 
CWI, the Netherlands, 1998.

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Henry Tirri, PhD.
Research Director, Prof. of Computer Science
Complex Systems Computation Group
Helsinki Institute for Information Technology (HIIT)
http://www.hiit.fi/henry.tirri; email: henry.tirri at hiit.fi
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