Nonconvex Online Support Vector Machines
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[1] Thorsten Joachims,et al. Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.
[2] John C. Platt,et al. Fast training of support vector machines using sequential minimal optimization, advances in kernel methods , 1999 .
[3] Greg Schohn,et al. Less is More: Active Learning with Support Vector Machines , 2000, ICML.
[4] S. Sathiya Keerthi,et al. Improvements to Platt's SMO Algorithm for SVM Classifier Design , 2001, Neural Computation.
[5] Alexander J. Smola,et al. Learning with Kernels: support vector machines, regularization, optimization, and beyond , 2001, Adaptive computation and machine learning series.
[6] Daphne Koller,et al. Support Vector Machine Active Learning with Applications to Text Classification , 2000, J. Mach. Learn. Res..
[7] Alan L. Yuille,et al. The Concave-Convex Procedure (CCCP) , 2001, NIPS.
[8] André Elisseeff,et al. Stability and Generalization , 2002, J. Mach. Learn. Res..
[9] Ingo Steinwart,et al. Sparseness of Support Vector Machines , 2003, J. Mach. Learn. Res..
[10] Fernando Pérez-Cruz,et al. Empirical risk minimization for support vector classifiers , 2003, IEEE Trans. Neural Networks.
[11] Anthony Widjaja,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2003, IEEE Transactions on Neural Networks.
[12] Nello Cristianini,et al. Kernel Methods for Pattern Analysis , 2003, ICTAI.
[13] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[14] Yoram Singer,et al. Leveraging the margin more carefully , 2004, ICML.
[15] Peter L. Bartlett,et al. Improved Generalization Through Explicit Optimization of Margins , 2000, Machine Learning.
[16] Jason Weston,et al. Fast Kernel Classifiers with Online and Active Learning , 2005, J. Mach. Learn. Res..
[17] Yufeng Liu,et al. Multicategory ψ-Learning and Support Vector Machine: Computational Tools , 2005 .
[18] Koby Crammer,et al. Robust Support Vector Machine Training via Convex Outlier Ablation , 2006, AAAI.
[19] Jason Weston,et al. Trading convexity for scalability , 2006, ICML.
[20] C. Lee Giles,et al. Learning on the border: active learning in imbalanced data classification , 2007, CIKM '07.
[21] Olivier Chapelle,et al. Training a Support Vector Machine in the Primal , 2007, Neural Computation.
[22] Jie Li,et al. Training robust support vector machine with smooth Ramp loss in the primal space , 2008, Neurocomputing.
[23] Nathan Srebro,et al. SVM optimization: inverse dependence on training set size , 2008, ICML '08.
[24] Christian Igel,et al. Second-Order SMO Improves SVM Online and Active Learning , 2008, Neural Computation.