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BMCBI
2007
194views more  BMCBI 2007»
13 years 9 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
ICADL
2003
Springer
159views Education» more  ICADL 2003»
14 years 2 months ago
Ontology Learning for Medical Digital Libraries
Ontologies play an important role in the Semantic Web as well as in digital library and knowledge portal applications. This project seeks to develop an automatic method to enrich e...
Chew-Hung Lee, Jin-Cheon Na, Christopher S. G. Kho...
NLPRS
2001
Springer
14 years 1 months ago
Learning Strategies In A Grammar Induction Framework
This work extends a semi-automatic grammar induction approach previously proposed in [1]. We investigate the use of Information Gain (IG) in place of Mutual Information (MI) for g...
Chin-Chung Wong, Helen M. Meng, Kai-Chung Siu
EMNLP
2010
13 years 7 months ago
Lessons Learned in Part-of-Speech Tagging of Conversational Speech
This paper examines tagging models for spontaneous English speech transcripts. We analyze the performance of state-of-the-art tagging models, either generative or discriminative, ...
Vladimir Eidelman, Zhongqiang Huang, Mary P. Harpe...
JMLR
2012
11 years 11 months ago
Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...
Avneesh Singh Saluja, Priya Krishnan Sundararajan,...