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» Maximal Vector Computation in Large Data Sets
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ICPR
2000
IEEE
14 years 5 days ago
Scaling-Up Support Vector Machines Using Boosting Algorithm
In the recent years support vector machines (SVMs) have been successfully applied to solve a large number of classification problems. Training an SVM, usually posed as a quadrati...
Dmitry Pavlov, Jianchang Mao, Byron Dom
BMCBI
2007
147views more  BMCBI 2007»
13 years 7 months ago
Improved residue contact prediction using support vector machines and a large feature set
Background: Predicting protein residue-residue contacts is an important 2D prediction task. It is useful for ab initio structure prediction and understanding protein folding. In s...
Jianlin Cheng, Pierre Baldi
ICDT
2001
ACM
124views Database» more  ICDT 2001»
14 years 6 days ago
Mining for Empty Rectangles in Large Data Sets
Abstract. Many data mining approaches focus on the discovery of similar (and frequent) data values in large data sets. We present an alternative, but complementary approach in whic...
Jeff Edmonds, Jarek Gryz, Dongming Liang, Ren&eacu...
ICML
2007
IEEE
14 years 8 months ago
Multiclass core vector machine
Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these appr...
S. Asharaf, M. Narasimha Murty, Shirish Krishnaj S...
TNN
2010
176views Management» more  TNN 2010»
13 years 2 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao