Support vector classification with input data uncertainty
Jinbo Bi, Tong Zhang
NeurIPS 2004
We introduce new two-sided Arnoldi recursions and use them to define a model reduction procedure for large, linear, time-invariant, multi-input/multi-output differential algebraic systems. We prove that this procedure has desirable moment matching properties. We define a corresponding model reduction procedure which is based on a band nonsymmetric Lanczos recursion and prove that if the deflation is exact and there are no breakdowns in the recursions, then these two model reduction procedures generate identical reduced-order systems. We prove similar equivalences for corresponding eigenelement procedures. We concentrate on the theoretical properties of the new algorithms.
Jinbo Bi, Tong Zhang
NeurIPS 2004
Joe H. Chow, Jane Cullum, et al.
IEEE Transactions on Power Apparatus and Systems
Tong Zhang, Rie Kubota Ando
NeurIPS 2005
Tong Zhang
ICML 2004