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» Choosing Multiple Parameters for Support Vector Machines
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ICCS
2001
Springer
14 years 7 days ago
Optimizing Sparse Matrix Computations for Register Reuse in SPARSITY
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to perform poorly on modern processors, largely because of its high ratio of memory op...
Eun-Jin Im, Katherine A. Yelick
SDM
2010
SIAM
226views Data Mining» more  SDM 2010»
13 years 9 months ago
Two-View Transductive Support Vector Machines
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
ICML
2006
IEEE
14 years 1 months ago
Multiclass reduced-set support vector machines
There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduce...
Benyang Tang, Dominic Mazzoni
CVPR
2006
IEEE
13 years 11 months ago
Region-based Image Annotation using Asymmetrical Support Vector Machine-based Multiple-Instance Learning
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning...
Changbo Yang, Ming Dong, Jing Hua
TNN
2008
152views more  TNN 2008»
13 years 7 months ago
Distributed Parallel Support Vector Machines in Strongly Connected Networks
We propose a distributed parallel support vector machine (DPSVM) training mechanism in a configurable network environment for distributed data mining. The basic idea is to exchange...
Yumao Lu, Vwani P. Roychowdhury, L. Vandenberghe