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» Maximal Vector Computation in Large Data Sets
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SDM
2008
SIAM
117views Data Mining» more  SDM 2008»
13 years 10 months ago
A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality
With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...
Yijun Sun, Sinisa Todorovic, Steve Goodison
ICPR
2010
IEEE
13 years 9 months ago
Adaptive Incremental Learning with an Ensemble of Support Vector Machines
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incre...
Marcelo N. Kapp, Robert Sabourin, Patrick Maupin
EOR
2007
95views more  EOR 2007»
13 years 9 months ago
A hybrid genetic algorithm for the two-dimensional single large object placement problem
In the two-dimensional single large object placement problem, we are given a rectangular master surface which has to be cut into a set of smaller rectangular items, with the aim o...
Eleni Hadjiconstantinou, Manuel Iori
SDM
2011
SIAM
232views Data Mining» more  SDM 2011»
12 years 12 months ago
A Sequential Dual Method for Structural SVMs
In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to computationa...
Shirish Krishnaj Shevade, Balamurugan P., S. Sunda...
GRID
2003
Springer
14 years 2 months ago
Applying Database Support for Large Scale Data Driven Science in Distributed Environments
There is a rapidly growing set of applications, referred to as data driven applications, in which analysis of large amounts of data drives the next steps taken by the scientist, e...
Sivaramakrishnan Narayanan, Ümit V. Ça...