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166
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ICML
2008
IEEE
16 years 4 months ago
Discriminative parameter learning for Bayesian networks
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...
WWW
2002
ACM
16 years 4 months ago
A machine learning based approach for table detection on the web
Table is a commonly used presentation scheme, especially for describing relational information. However, table understanding remains an open problem. In this paper, we consider th...
Yalin Wang, Jianying Hu
125
Voted
BIBE
2007
IEEE
162views Bioinformatics» more  BIBE 2007»
15 years 10 months ago
An Investigation into the Feasibility of Detecting Microscopic Disease Using Machine Learning
— The prognosis for many cancers could be improved dramatically if they could be detected while still at the microscopic disease stage. We are investigating the possibility of de...
Mary Qu Yang, Jack Y. Yang
141
Voted
AIME
2009
Springer
15 years 1 months ago
Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach
Lung cancer represents the most deadly type of malignancy. In this work we propose a machine learning approach to segmenting lung tumours in Positron Emission Tomography (PET) scan...
Aliaksei Kerhet, Cormac Small, Harvey Quon, Terenc...
168
Voted
BMCBI
2008
220views more  BMCBI 2008»
15 years 3 months ago
Gene prediction in metagenomic fragments: A large scale machine learning approach
Background: Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. ...
Katharina J. Hoff, Maike Tech, Thomas Lingner, Rol...