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» Determining Automatically the Size of Learned Ontologies
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ECML
2003
Springer
13 years 10 months ago
A Generative Model for Semantic Role Labeling
Determining the semantic role of sentence constituents is a key task in determining sentence meanings lying behind a veneer of variant syntactic expression. We present a model of n...
Cynthia A. Thompson, Roger Levy, Christopher D. Ma...
ICB
2009
Springer
159views Biometrics» more  ICB 2009»
13 years 12 months ago
Multilinear Tensor-Based Non-parametric Dimension Reduction for Gait Recognition
The small sample size problem and the difficulty in determining the optimal reduced dimension limit the application of subspace learning methods in the gait recognition domain. To...
Changyou Chen, Junping Zhang, Rudolf Fleischer
ICCAD
2008
IEEE
107views Hardware» more  ICCAD 2008»
13 years 12 months ago
Importance sampled circuit learning ensembles for robust analog IC design
This paper presents ISCLEs, a novel and robust analog design method that promises to scale with Moore’s Law, by doing boosting-style importance sampling on digital-sized circuit...
Peng Gao, Trent McConaghy, Georges G. E. Gielen
BMCBI
2007
129views more  BMCBI 2007»
13 years 5 months ago
Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach
Background: Incorrectly annotated sequence data are becoming more commonplace as databases increasingly rely on automated techniques for annotation. Hence, there is an urgent need...
Carson M. Andorf, Drena Dobbs, Vasant Honavar
NN
2002
Springer
125views Neural Networks» more  NN 2002»
13 years 5 months ago
Generalized relevance learning vector quantization
We propose a new scheme for enlarging generalized learning vector quantization (GLVQ) with weighting factors for the input dimensions. The factors allow an appropriate scaling of ...
Barbara Hammer, Thomas Villmann