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BMCBI
2006
173views more  BMCBI 2006»
14 years 11 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen
ICML
2003
IEEE
15 years 12 months ago
Unsupervised Learning with Permuted Data
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
Sergey Kirshner, Sridevi Parise, Padhraic Smyth
KDD
2010
ACM
249views Data Mining» more  KDD 2010»
15 years 1 months ago
Semi-supervised sparse metric learning using alternating linearization optimization
In plenty of scenarios, data can be represented as vectors mathematically abstracted as points in a Euclidean space. Because a great number of machine learning and data mining app...
Wei Liu, Shiqian Ma, Dacheng Tao, Jianzhuang Liu, ...
KES
2007
Springer
15 years 5 months ago
Inductive Concept Retrieval and Query Answering with Semantic Knowledge Bases Through Kernel Methods
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...
Nicola Fanizzi, Claudia d'Amato
CIKM
2008
Springer
15 years 1 months ago
Identifying table boundaries in digital documents via sparse line detection
Most prior work on information extraction has focused on extracting information from text in digital documents. However, often, the most important information being reported in an...
Ying Liu, Prasenjit Mitra, C. Lee Giles