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ESANN
1997
13 years 11 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...
NIPS
2004
13 years 11 months ago
Modeling Conversational Dynamics as a Mixed-Memory Markov Process
In this work, we quantitatively investigate the ways in which a given person influences the joint turn-taking behavior in a conversation. After collecting an auditory database of ...
Tanzeem Choudhury, Sumit Basu
UAI
1998
13 years 11 months ago
Structured Reachability Analysis for Markov Decision Processes
Recent research in decision theoretic planning has focussedon making the solution of Markov decision processes (MDPs) more feasible. We develop a family of algorithms for structur...
Craig Boutilier, Ronen I. Brafman, Christopher W. ...
ICDAR
2009
IEEE
13 years 7 months ago
Lexicon-Based Word Recognition Using Support Vector Machine and Hidden Markov Model
Hybrid of Neural Network (NN) and Hidden Markov Model (HMM) has been popular in word recognition, taking advantage of NN discriminative property and HMM representational capabilit...
Abdul Rahim Ahmad, Christian Viard-Gaudin, Marzuki...
ECML
2006
Springer
14 years 1 months ago
TildeCRF: Conditional Random Fields for Logical Sequences
Abstract. Conditional Random Fields (CRFs) provide a powerful instrument for labeling sequences. So far, however, CRFs have only been considered for labeling sequences over flat al...
Bernd Gutmann, Kristian Kersting