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KDD
2004
ACM
124views Data Mining» more  KDD 2004»
16 years 3 days ago
Incorporating prior knowledge with weighted margin support vector machines
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
Xiaoyun Wu, Rohini K. Srihari
SIGIR
2003
ACM
15 years 12 months ago
Question classification using support vector machines
Question classification is very important for question answering. This paper presents our research work on automatic question classification through machine learning approaches. W...
Dell Zhang, Wee Sun Lee
ICML
2007
IEEE
16 years 7 months ago
Support cluster machine
For large-scale classification problems, the training samples can be clustered beforehand as a downsampling pre-process, and then only the obtained clusters are used for training....
Bin Li, Mingmin Chi, Jianping Fan, Xiangyang Xue
ICML
2007
IEEE
16 years 7 months ago
Beamforming using the relevance vector machine
Beamformers are spatial filters that pass source signals in particular focused locations while suppressing interference from elsewhere. The widely-used minimum variance adaptive b...
David P. Wipf, Srikantan S. Nagarajan
151
Voted
ICML
2006
IEEE
16 years 7 months ago
Deterministic annealing for semi-supervised kernel machines
An intuitive approach to utilizing unlabeled data in kernel-based classification algorithms is to simply treat unknown labels as additional optimization variables. For marginbased...
Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chape...