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BMCBI
2007
178views more  BMCBI 2007»
15 years 6 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
ICS
2010
Tsinghua U.
15 years 11 months ago
Large-scale FFT on GPU clusters
A GPU cluster is a cluster equipped with GPU devices. Excellent acceleration is achievable for computation-intensive tasks (e.g. matrix multiplication and LINPACK) and bandwidth-i...
Yifeng Chen, Xiang Cui, Hong Mei
KDD
2005
ACM
127views Data Mining» more  KDD 2005»
16 years 7 months ago
Detection of emerging space-time clusters
We propose a new class of spatio-temporal cluster detection methods designed for the rapid detection of emerging space-time clusters. We focus on the motivating application of pro...
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabh...
VLDB
2007
ACM
164views Database» more  VLDB 2007»
16 years 7 months ago
A new intrusion detection system using support vector machines and hierarchical clustering
Whenever an intrusion occurs, the security and value of a computer system is compromised. Network-based attacks make it difficult for legitimate users to access various network ser...
Latifur Khan, Mamoun Awad, Bhavani M. Thuraisingha...
208
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JMLR
2002
111views more  JMLR 2002»
15 years 6 months ago
The Learning-Curve Sampling Method Applied to Model-Based Clustering
We examine the learning-curve sampling method, an approach for applying machinelearning algorithms to large data sets. The approach is based on the observation that the computatio...
Christopher Meek, Bo Thiesson, David Heckerman