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ECML
2006
Springer
14 years 5 days ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi
APBC
2004
132views Bioinformatics» more  APBC 2004»
13 years 10 months ago
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
Liang Goh, Qun Song, Nikola K. Kasabov
BIBM
2009
IEEE
192views Bioinformatics» more  BIBM 2009»
14 years 3 months ago
A Multi-task Feature Selection Filter for Microarray Classification
A major challenge in microarray classification and biomarker discovery is dealing with small-sample high-dimensional data where the number of genes used as features is typically o...
Liang Lan, Slobodan Vucetic
PAMI
2010
184views more  PAMI 2010»
13 years 7 months ago
Accurate Image Search Using the Contextual Dissimilarity Measure
— This paper introduces the contextual dissimilarity measure which significantly improves the accuracy of bag-offeatures based image search. Our measure takes into account the l...
Herve Jegou, Cordelia Schmid, Hedi Harzallah, Jako...
ICIP
2003
IEEE
14 years 10 months ago
Performance evaluation of Euclidean/correlation-based relevance feedback algorithms in content-based image retrieval systems
In this paper, we evaluate and investigate two main types of relevance feedback algorithms; the Euclidean and the correlation?based approaches. In the first case, we examine heuri...
Anastasios D. Doulamis, Nikolaos D. Doulamis