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KDD
2000
ACM
133views Data Mining» more  KDD 2000»
13 years 11 months ago
Data selection for support vector machine classifiers
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
Glenn Fung, Olvi L. Mangasarian
BIBE
2007
IEEE
162views Bioinformatics» more  BIBE 2007»
14 years 2 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
CIVR
2007
Springer
192views Image Analysis» more  CIVR 2007»
14 years 1 months ago
Texture retrieval based on a non-parametric measure for multivariate distributions
In the present study, an efficient strategy for retrieving texture images from large texture databases is introduced and studied within a distributional-statistical framework. Our...
Vasileios K. Pothos, Christos Theoharatos, George ...
WWW
2011
ACM
13 years 2 months ago
Prophiler: a fast filter for the large-scale detection of malicious web pages
Malicious web pages that host drive-by-download exploits have become a popular means for compromising hosts on the Internet and, subsequently, for creating large-scale botnets. In...
Davide Canali, Marco Cova, Giovanni Vigna, Christo...
NIPS
2003
13 years 9 months ago
Minimax Embeddings
Spectral methods for nonlinear dimensionality reduction (NLDR) impose a neighborhood graph on point data and compute eigenfunctions of a quadratic form generated from the graph. W...
Matthew Brand