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SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
14 years 11 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur
COLT
2010
Springer
14 years 10 months ago
Forest Density Estimation
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
80
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ICPR
2010
IEEE
14 years 10 months ago
Performance Evaluation of Automatic Feature Discovery Focused within Error Clusters
We report performance evaluation of our automatic feature discovery method on the publicly available Gisette dataset: a set of 29 features discovered by our method ranks 129 among...
Sui-Yu Wang, Henry S. Baird
IDEAL
2010
Springer
14 years 10 months ago
Trajectory Based Behavior Analysis for User Verification
Many of our activities on computer need a verification step for authorized access. The goal of verification is to tell apart the true account owner from intruders. We propose a gen...
Hsing-Kuo Pao, Hong-Yi Lin, Kuan-Ta Chen, Junaidil...
ICDM
2010
IEEE
200views Data Mining» more  ICDM 2010»
14 years 10 months ago
Bayesian Maximum Margin Clustering
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
Bo Dai, Baogang Hu, Gang Niu