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ISNN
2004
Springer
16 years 1 days ago
Fuzzy-Kernel Learning Vector Quantization
This paper presents an unsupervised fuzzy-kernel learning vector quantization algorithm called FKLVQ. FKLVQ is a batch type of clustering learning network by fusing the batch learn...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
ICANN
2009
Springer
15 years 11 months ago
Constrained Learning Vector Quantization or Relaxed k-Separability
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Marek Grochowski, Wlodzislaw Duch
191
Voted
ICANN
2001
Springer
15 years 11 months ago
Incremental Support Vector Machine Learning: A Local Approach
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Liva Ralaivola, Florence d'Alché-Buc
ACSAC
2004
IEEE
15 years 10 months ago
RACOON: Rapidly Generating User Command Data For Anomaly Detection From Customizable Templates
One of the biggest obstacles faced by user command based anomaly detection techniques is the paucity of data. Gathering command data is a slow process often spanning months or yea...
Ramkumar Chinchani, Aarthie Muthukrishnan, Madhusu...
KDD
2004
ACM
196views Data Mining» more  KDD 2004»
16 years 7 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...