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» Sublinear Optimization for Machine Learning
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TIP
2008
175views more  TIP 2008»
13 years 7 months ago
Customizing Kernel Functions for SVM-Based Hyperspectral Image Classification
Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available ...
Baofeng Guo, Steve R. Gunn, Robert I. Damper, Jame...
CCE
2005
13 years 7 months ago
Selecting maximally informative genes
Microarray experiments are emerging as one of the main driving forces in modern biology. By allowing the simultaneous monitoring of the expression of the entire genome for a given...
Ioannis P. Androulakis
INFORMATICASI
1998
122views more  INFORMATICASI 1998»
13 years 7 months ago
Experimental Evaluation of Three Partition Selection Criteria for Decision Table Decomposition
Decision table decomposition is a machine learning approach that decomposes a given decision table into an equivalent hierarchy of decision tables. The approach aims to discover d...
Blaz Zupan, Marko Bohanec
JCS
2002
103views more  JCS 2002»
13 years 7 months ago
Toward Cost-Sensitive Modeling for Intrusion Detection and Response
Intrusion detection systems (IDSs) must maximize the realization of security goals while minimizing costs. In this paper, we study the problem of building cost-sensitive intrusion...
Wenke Lee, Wei Fan, Matthew Miller, Salvatore J. S...
MICCAI
2010
Springer
13 years 6 months ago
3D Knowledge-Based Segmentation Using Pose-Invariant Higher-Order Graphs
Segmentation is a fundamental problem in medical image analysis. The use of prior knowledge is often considered to address the ill-posedness of the process. Such a process consists...
Chaohui Wang, Olivier Teboul, Fabrice Michel, Salm...