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ICDE
2008
IEEE
203views Database» more  ICDE 2008»
14 years 9 months ago
Training Linear Discriminant Analysis in Linear Time
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. It has been widely used in many fields of information proces...
Deng Cai, Xiaofei He, Jiawei Han
RSFDGRC
2005
Springer
156views Data Mining» more  RSFDGRC 2005»
14 years 1 months ago
Intrusion Detection System Based on Multi-class SVM
In this paper, we propose a new intrusion detection model, which keeps advantages of existing misuse detection model and anomaly detection model and resolves their problems. This ...
Hansung Lee, Jiyoung Song, Daihee Park
ICDE
2009
IEEE
156views Database» more  ICDE 2009»
14 years 9 months ago
Online Anomaly Prediction for Robust Cluster Systems
In this paper, we present a stream-based mining algorithm for online anomaly prediction. Many real-world applications such as data stream analysis requires continuous cluster opera...
Xiaohui Gu, Haixun Wang
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
KDD
2006
ACM
115views Data Mining» more  KDD 2006»
14 years 8 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...