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» Data Mining via Support Vector Machines
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IPPS
2003
IEEE
15 years 9 months ago
A Compilation Framework for Distributed Memory Parallelization of Data Mining Algorithms
With the availability of large datasets in a variety of scientific and commercial domains, data mining has emerged as an important area within the last decade. Data mining techni...
Xiaogang Li, Ruoming Jin, Gagan Agrawal
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
16 years 4 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
ICML
2010
IEEE
15 years 5 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
SDM
2009
SIAM
191views Data Mining» more  SDM 2009»
16 years 1 months ago
Adaptive Concept Drift Detection.
An established method to detect concept drift in data streams is to perform statistical hypothesis testing on the multivariate data in the stream. Statistical decision theory off...
Anton Dries, Ulrich Rückert
ICML
2001
IEEE
16 years 5 months ago
Learning with the Set Covering Machine
We generalize the classical algorithms of Valiant and Haussler for learning conjunctions and disjunctions of Boolean attributes to the problem of learning these functions over arb...
Mario Marchand, John Shawe-Taylor