Benchmarking of learning algorithms

information repository page

Abstract: Proper benchmarking of (neural network and other) learning architectures is a prerequisite for orderly progress in this field. In many published papers deficiencies can be observed in the benchmarking that is performed.
A workshop about NN benchmarking at NIPS*95 addressed the status quo of benchmarking, common errors and how to avoid them, currently existing benchmark collections, and, most prominently, a new benchmarking facility including a results database.
This page contains pointers to written versions or slides of most of the talks given at the workshop plus some related material. The page is intended to be a repository for such information to be used as a reference by researchers in the field. Note that most links lead to Postscript documents. Please send any additions or corrections you might have to Lutz Prechelt (

What's new?

Workshop Chairs:

Assessment of the status quo:


Benchmarking facilities:

Other sources of data:

Other related information:

This page has received a Key Resource award in the Neural Networks topic.
Please send additions and corrections to Lutz Prechelt (
To NIPS homepage.

Last modified: Wed Mar 29 18:09:30 MET DST 2000