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IJCNN
2006
IEEE
15 years 10 months ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li
COLT
2005
Springer
15 years 10 months ago
General Polynomial Time Decomposition Algorithms
We present a general decomposition algorithm that is uniformly applicable to every (suitably normalized) instance of Convex Quadratic Optimization and efficiently approaches an o...
Nikolas List, Hans-Ulrich Simon
AUTOMATICA
2008
98views more  AUTOMATICA 2008»
15 years 4 months ago
An algorithm for bounded-error identification of nonlinear systems based on DC functions
This paper presents a guaranteed method for the parameter estimation of nonlinear models in a bounded-error context. This method is based on functions which consists of the differ...
J. M. Bravo, T. Alamo, M. J. Redondo, Eduardo F. C...
SIAMJO
2008
104views more  SIAMJO 2008»
15 years 4 months ago
A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance
This paper concerns a fractional function of the form xT a/ xT Bx, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, an...
Seung-Jean Kim, Stephen P. Boyd
PATMOS
2007
Springer
15 years 10 months ago
Optimization for Real-Time Systems with Non-convex Power Versus Speed Models
Abstract. Until now, the great majority of research in low-power systems has assumed a convex power model. However, recently, due to the confluence of emerging technological and ar...
Ani Nahapetian, Foad Dabiri, Miodrag Potkonjak, Ma...