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ECML
2006
Springer
15 years 1 months 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»
14 years 11 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»
15 years 4 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»
14 years 8 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...
82
Voted
ICIP
2003
IEEE
15 years 11 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