To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
The one-dimensional functional equation g(y(t)) = cg(z(t)) with known functions y and z and constant c is considered. The indeterminacies are calculated, and an algorithm for appro...
The computation and memory required for kernel machines with N training samples is at least O(N2 ). Such a complexity is significant even for moderate size problems and is prohibi...
Changjiang Yang, Ramani Duraiswami, Larry S. Davis
In this paper, a unified framework for representing uncertain information based on the notion of an interval structure is proposed. It is shown that the lower and upper approximat...
A controller change from a current controller which stabilises the plant to a new controller, designed on the basis of an approximate model of the plant and with guaranteed bounds...
A. Lecchini, Alexander Lanzon, Brian D. O. Anderso...