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TNN
1998
123views more  TNN 1998»
13 years 8 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
ICDM
2005
IEEE
134views Data Mining» more  ICDM 2005»
14 years 2 months ago
A Preference Model for Structured Supervised Learning Tasks
The preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, su...
Fabio Aiolli
WSOM
2009
Springer
14 years 3 months ago
Towards Semi-supervised Manifold Learning: UKR with Structural Hints
We explore generic mechanisms to introduce structural hints into the method of Unsupervised Kernel Regression (UKR) in order to learn representations of data sequences in a semi-su...
Jan Steffen, Stefan Klanke, Sethu Vijayakumar, Hel...
APN
2010
Springer
14 years 12 days ago
GreatSPN Enhanced with Decision Diagram Data Structures
Decision diagrams (DDs) have made their way into Petri net (PN) tools either in the form of new tools (usually designed from scratch to use DDs) or as enhancements to existing tool...
Junaid Babar, Marco Beccuti, Susanna Donatelli, An...
COLING
2010
13 years 3 months ago
Active Deep Networks for Semi-Supervised Sentiment Classification
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...
Shusen Zhou, Qingcai Chen, Xiaolong Wang