Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at finding irregularlyshaped clusters in data. The input to...
Spectral expansion and matrix analytic methods are important solution mechanisms for matrix polynomial equations. These equations are encountered in the steady-state analysis of M...
In this paper, a method is introduced how to process the Discrete Fourier Transform (DFT) by a singlelayer neural network with a linear transfer function. By implementing the sugg...
Multiple Kernel Learning (MKL) can be formulated as a convex-concave minmax optimization problem, whose saddle point corresponds to the optimal solution to MKL. Most MKL methods e...
Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu...
Abstract: The quantum adversary method is one of the most versatile lower-bound methods for quantum algorithms. We show that all known variants of this method are equivalent: spect...