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B. Scholkopf and A. Smola," Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond," Cambridge, MA: MIT Press, 2002.
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The p-norm generalization of the LMS algorithm for adaptive filtering
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Online learning with kernels
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J. Kivinen, A. Smola, and R. Williamson, "Online learning with kernels," IEEE Transactions on Signal Processing, vol. 52, pp. 2165-2176, 2004.
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IEEE Transactions on Signal Processing
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Kivinen, J.1
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Support vector machine techniques for nonlinear equalization
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L. Cheng, M. Gong, D. Schuurmans, and T. Caelli, "Real-time Discriminative Background Subtraction," IEEE Transactions on Image Processing , 2011. DOI: 10.1109/TIP.2010.2087764.
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Cheng, L.1
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6
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Estimating the support of a high-dimensional distribution
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B. Schölkopf, J. Platt, J. Shawe-Taylor, A. J. Smola, and R. C. Williamson, "Estimating the support of a high-dimensional distribution," Neural Compututation, vol. 13, no. 7, 2001.
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An online support vector machine for abnormal events detection
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M. Davy , F. Desobry, A. Gretton and C. Doncarli, " An Online Support Vector Machine for Abnormal Events Detection," Signal Processing, vol. 86, pp. 2009-2025, 2006.
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S. Boyd, and L. Vandenberghe, "Convex Optimization, " Cambridge University Press, Available at http://www.stanford.edu/ boyd/cvxbook/, 2004.
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A generalized represnter theory
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B. Scholkopf, R. Herbric, and A.J.Saola, " A generalized represnter theory ," in proceedings of the Annual Conference on Computational Learning Theory, pp. 416-426, 2001.
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