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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://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 filtering mechanism (LASVM-I) based on approximating nonconvex behavior in convex ...Cited by: 108
https://core.ac.uk/display/23803524
Editor: In this paper, we propose a non-convex online Support Vector Machine (SVM) algorithm (LASVM-NC) based on the Ramp Loss, which has 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 non-convex behavior in convex ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.409.8716
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Editor: In this paper, we propose a non-convex online Support Vector Machine (SVM) algorithm (LASVM-NC) based on the Ramp Loss, which has 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 non ...
https://people.cs.umass.edu/~hajiesmaili/files/Sigmetrics182.pdf
framework fails in modeling such case. In addition, there are extensive machine learning research focusing on non-convex loss functions in large margin classifiers [12, 37, 49]. In [12, 37], non-convex online Support Vector Machine (SVM) models has been studied which adopts a non-convex loss
https://www.academia.edu/1151273/Non-Convex_Online_Support_Vector_Machines
Non-Convex Online Support Vector Machines
https://www.researchgate.net/publication/224141988_Nonconvex_Online_Support_Vector_Machines
For more examples of non-convex applications, one can refer to [11] [13]which discuss non-convex online Support Vector Machines (SVMs)[42]and non-convex …
http://web.mit.edu/seyda/www/Papers/GHC06_ACMSRC_abstract.pdf
Fast Classification with Online Support Vector Machines Seyda Ertekin ... LASVM with Active Learning and Non-Convex Loss Function ... Giles L. Non Convex Online Support Vector Machines & Active Learning. Working paper, IST, The Pennsylvania State University, 2005 .
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
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