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ESANN
1997
15 years 5 months ago
Extraction of crisp logical rules using constrained backpropagation networks
Two recently developed methods for extraction of crisp logical rules from neural networks trained with backpropagation algorithm are compared. Both methods impose constraints on th...
Wlodzislaw Duch, Rafal Adamczak, Krzysztof Grabcze...
JMLR
2010
227views more  JMLR 2010»
15 years 2 months ago
PyBrain
PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easyto-use yet still powerful algorithms for machine learning tasks, including a vari...
Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, M...
TNN
1998
123views more  TNN 1998»
15 years 4 months ago
A general framework for adaptive processing of data structures
—A structured organization of information is typically required by symbolic processing. On the other hand, most connectionist models assume that data are organized according to r...
Paolo Frasconi, Marco Gori, Alessandro Sperduti
NIPS
1992
15 years 5 months ago
Network Structuring and Training Using Rule-Based Knowledge
We demonstrate in this paper how certain forms of rule-based knowledge can be used to prestructure a neural network of normalized basis functions and give a probabilistic interpre...
Volker Tresp, Jürgen Hollatz, Subutai Ahmad
ICANN
2009
Springer
15 years 11 months ago
Logics and Networks for Human Reasoning
We propose to model human reasoning tasks using completed logic programs interpreted under the three-valued Lukasiewicz semantics. Given an appropriate immediate consequence operat...
Steffen Hölldobler, Carroline Dewi Puspa Kenc...