Searching for Nonconvex Online Support Vector Machines information? Find all needed info by using official links provided below.
https://www.researchgate.net/publication/224141988_Nonconvex_Online_Support_Vector_Machines
In this paper, we propose a nonconvex online Support Vector Machine (SVM) algorithm (LASVM-NC) based on the Ramp Loss, which has the strong ability of suppressing the influence of outliers.
https://dl.acm.org/citation.cfm?id=1936584
In this paper, we propose a nonconvex online Support Vector Machine (SVM) algorithm (LASVM-NC) based on the Ramp Loss, which has the strong ability of suppressing the influence of outliers. Then, again in the online learning setting, we propose an outlier ...Cited by: 108
https://ieeexplore.ieee.org/document/5473234/
May 27, 2010 · Abstract: In this paper, we propose a nonconvex online Support Vector Machine (SVM) algorithm (LASVM-NC) based on the Ramp Loss, which has the strong ability of suppressing the influence of outliers. Then, again in the online learning setting, we propose an outlier filtering mechanism (LASVM-I) based on approximating nonconvex behavior in convex optimization.Cited by: 108
http://web.mit.edu/seyda/www/Papers/2009_a.pdf
Ignorance is Bliss: Non-Convex Online Support Vector Machines informativeness of the data prior to the processing by the learner becomes possible. We implement an online SVM training with non-convex loss function (LASVM-NC), which yields a significant speed improvement in training and builds a sparser model, hence resulting in
https://www.semanticscholar.org/paper/Nonconvex-Online-Support-Vector-Machines-Ertekin-Bottou/04c348d4fd08fddf5912a6ed946109a297708789
In this paper, we propose a nonconvex online Support Vector Machine (SVM) algorithm (LASVM-NC) based on the Ramp Loss, which has the strong ability of suppressing the influence of outliers. Then, again in the online learning setting, we propose an outlier filtering mechanism (LASVM-I) based on approximating nonconvex behavior in convex optimization. These two algorithms are built upon …
https://core.ac.uk/display/22005134
Abstract. Abstract—In this paper, we propose a nonconvex online Support Vector Machine (SVM) algorithm (LASVM-NC) based on the Ramp Loss, which has the strong ability of suppressing the influence of outliers.
https://avesis.metu.edu.tr/yayin/8de8e3c2-a3ed-4a58-bab5-08cbf4b71697/nonconvex-online-support-vector-machines
In this paper, we propose a nonconvex online Support Vector Machine (SVM) algorithm (LASVM-NC) based on the Ramp Loss, which has the strong ability of suppressing the influence of outliers. Then, again in the online learning setting, we propose an outlier filtering mechanism (LASVM-I) based on approximating nonconvex behavior in convex ...Cited by: 108
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.207.8530
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract—In this paper, we propose a nonconvex online Support Vector Machine (SVM) algorithm (LASVM-NC) based on the Ramp Loss, which has the strong ability of suppressing the influence of outliers. Then, again in the online learning setting, we propose an outlier filtering mechanism (LASVM-I) based on approximating ...
https://academic.oup.com/bioinformatics/article/22/1/88/218231
Oct 25, 2005 · Results: In this paper we develop a novel type of regularization in support vector machines (SVMs) to identify important genes for cancer classification. A special nonconvex penalty, called the smoothly clipped absolute deviation penalty, is imposed on the hinge loss function in the SVM.Cited by: 295
https://www.academia.edu/1151273/Non-Convex_Online_Support_Vector_Machines
Non-Convex Online Support Vector Machines
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