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» Incremental Training of Multiclass Support Vector Machines
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AAAI
2006
14 years 10 months ago
Robust Support Vector Machine Training via Convex Outlier Ablation
One of the well known risks of large margin training methods, such as boosting and support vector machines (SVMs), is their sensitivity to outliers. These risks are normally mitig...
Linli Xu, Koby Crammer, Dale Schuurmans
IJCNN
2008
IEEE
15 years 3 months ago
Sparse support vector machines trained in the reduced empirical feature space
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
Kazuki Iwamura, Shigeo Abe
ICASSP
2011
IEEE
14 years 1 months ago
Fall detection in a smart room by using a fuzzy one class support vector machine and imperfect training data
In this paper, we propose an efficient and robust fall detection system by using a fuzzy one class support vector machine based on video information. Two cameras are used to capt...
Miao Yu, Syed Mohsen Naqvi, Adel Rhuma, Jonathon A...
ICANN
2001
Springer
15 years 1 months ago
Fast Training of Support Vector Machines by Extracting Boundary Data
Support vector machines have gotten wide acceptance for their high generalization ability for real world applications. But the major drawback is slow training for classification p...
Shigeo Abe, Takuya Inoue
SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
15 years 6 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic