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ICML
2003
IEEE
15 years 12 months ago
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
Zhihua Zhang
ICML
2002
IEEE
15 years 12 months ago
Kernels for Semi-Structured Data
Semi-structured data such as XML and HTML is attracting considerable attention. It is important to develop various kinds of data mining techniques that can handle semistructured d...
Hisashi Kashima, Teruo Koyanagi
IJCNN
2006
IEEE
15 years 5 months ago
Kernel Based Functional Gene Grouping
Abstract— During the last years, high throughput experiments have become very popular. During the analysis of such data the need for a functional grouping of genes arises. In thi...
Holger Fröhlich, Nora Speer, Christian Spieth...
SPIRE
2005
Springer
15 years 4 months ago
Deriving TF-IDF as a Fisher Kernel
The Dirichlet compound multinomial (DCM) distribution has recently been shown to be a good model for documents because it captures the phenomenon of word burstiness, unlike standar...
Charles Elkan
AUSDM
2006
Springer
102views Data Mining» more  AUSDM 2006»
15 years 2 months ago
Weighted Kernel Model For Text Categorization
Traditional bag-of-words model and recent wordsequence kernel are two well-known techniques in the field of text categorization. Bag-of-words representation neglects the word orde...
Lei Zhang, Debbie Zhang, Simeon J. Simoff, John K....