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ICASSP
2011
IEEE
7 years 10 months ago
Effective background data selection in SVM speaker recognition for unseen test environment: More is not always better
This study focuses on determining a procedure to select effective negative examples for development of improved Support Vector Machine (SVM) based speaker recognition. Selection o...
Jun-Won Suh, Yun Lei, Wooil Kim, John H. L. Hansen
TR
2010
204views Hardware» more  TR 2010»
8 years 29 days ago
Anomaly Detection Through a Bayesian Support Vector Machine
This paper investigates the use of a one-class support vector machine algorithm to detect the onset of system anomalies, and trend output classification probabilities, as a way to ...
Vasilis A. Sotiris, Peter W. Tse, Michael Pecht
IJBRA
2010
133views more  IJBRA 2010»
8 years 3 months ago
Scalable biomedical Named Entity Recognition: investigation of a database-supported SVM approach
This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features and ...
Mona Soliman Habib, Jugal Kalita
ICTAI
2010
IEEE
8 years 4 months ago
Support Vector Methods for Sentence Level Machine Translation Evaluation
Recent work in the field of machine translation (MT) evaluation suggests that sentence level evaluation based on machine learning (ML) can outperform the standard metrics such as B...
Antoine Veillard, Elvina Melissa, Cassandra Theodo...
IJPRAI
2010
151views more  IJPRAI 2010»
8 years 4 months ago
Structure-Embedded AUC-SVM
: AUC-SVM directly maximizes the area under the ROC curve (AUC) through minimizing its hinge loss relaxation, and the decision function is determined by those support vector sample...
Yunyun Wang, Songcan Chen, Hui Xue
TIP
2008
128views more  TIP 2008»
8 years 6 months ago
Wavelet Frame Accelerated Reduced Support Vector Machines
In this paper, a novel method for reducing the runtime complexity of a support vector machine classifier is presented. The new training algorithm is fast and simple. This is achiev...
Matthias Rätsch, Gerd Teschke, Sami Romdhani,...
PRL
2006
114views more  PRL 2006»
8 years 6 months ago
Incremental training of support vector machines using hyperspheres
In the conventional incremental training of support vector machines, candidates for support vectors tend to be deleted if the separating hyperplane rotates as the training data ar...
Shinya Katagiri, Shigeo Abe
JMLR
2008
104views more  JMLR 2008»
8 years 6 months ago
Nearly Uniform Validation Improves Compression-Based Error Bounds
This paper develops bounds on out-of-sample error rates for support vector machines (SVMs). The bounds are based on the numbers of support vectors in the SVMs rather than on VC di...
Eric Bax
CORR
2008
Springer
142views Education» more  CORR 2008»
8 years 6 months ago
A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
Danny Bickson, Elad Yom-Tov, Danny Dolev
GRC
2008
IEEE
8 years 7 months ago
Adaptive and Iterative Least Squares Support Vector Regression based on Quadratic Renyi Entropy
An adaptive and iterative LSSVR algorithm based on quadratic Renyi entropy is presented in this paper. LS-SVM loses the sparseness of support vector which is one of the important ...
Jingqing Jiang, Chuyi Song, Haiyan Zhao, Chunguo W...
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