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» Data Mining via Support Vector Machines
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NOMS
2006
IEEE
15 years 3 months ago
Predicting Machine Availabilities in Desktop Pools
—This paper describes a study of predicting machine availabilities and user presence in a pool of desktop computers. The study is based on historical traces collected from 32 mac...
Artur Andrzejak, Patrício Domingues, Lu&iac...
KDD
2008
ACM
246views Data Mining» more  KDD 2008»
15 years 10 months ago
Direct mining of discriminative and essential frequent patterns via model-based search tree
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...
KAIS
2008
99views more  KAIS 2008»
14 years 9 months ago
Privacy-preserving SVM classification
Classical data mining algorithms implicitly assume complete access to all data, either in centralized or federated form. However, privacy and security concerns often prevent sharin...
Jaideep Vaidya, Hwanjo Yu, Xiaoqian Jiang
KDD
2006
ACM
170views Data Mining» more  KDD 2006»
15 years 10 months ago
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
This paper describes a novel classification method for computer aided detection (CAD) that identifies structures of interest from medical images. CAD problems are challenging larg...
Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Tosh...
SDM
2008
SIAM
161views Data Mining» more  SDM 2008»
14 years 11 months ago
Efficient Maximum Margin Clustering via Cutting Plane Algorithm
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
Bin Zhao, Fei Wang, Changshui Zhang