— 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 ...
We present a general decomposition algorithm that is uniformly applicable to every (suitably normalized) instance of Convex Quadratic Optimization and efficiently approaches an o...
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...
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...
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...