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This paper describes a general purpose method for solving convex optimization problems in a distributed computing environment. In particular, if the problem data includes a large linear operator or ma...
We consider the problem of minimizing a sum of non-convex functions over a compact domain, subject to linear inequality and equality constraints. We consider approximate solutions obtained by solving ...
This paper describes Convex.jl, a convex optimization modeling framework in Julia. Convex.jl translates problems from a user-friendly functional language into an abstract syntax tree describing the pr...
We consider the switched-affine optimal control problem, i.e., the problem of selecting a sequence of affine dynamics from a finite set in order to minimize a sum of convex functions of the system sta...
We consider the NP-hard problem of minimizing a convex quadratic function over the integer lattice Zn. We present a semidefinite programming (SDP) method for obtaining a nontrivial lower bound on the ...
A pseudorandom function F : K X ! Y is said to be key homomorphic if given F(k1; x) and F(k2; x) there is an ecient algorithm to compute F(k1  k2; x), where  denotes a group operation on k1 and ...
In light of such an inherent difficulty, any meaningful notion of function privacy must be based on the minimal assumption that, from the adversary's point of view, identities that correspond to...
Slow feature analysis (SFA) is a new unsupervised algorithm to learn nonlinear functions that extract slowly varying signals out of the input data. In this paper we describe its application to pattern...
The discrimination technique for estimating the parameters of Gaussian mixtures that is based on the Extended Baum transformations (EB) has had significant impact on the speech recognition community. ...
The Hudson et al Test (1983) has demonstrated an adequate interna1 consistency (Alpha = 0.81) as well as its validity for measuring sexual attitudes. This is due to the possibility of finding - by m...
为了解决以往正则最小二乘法求权重向量时遇到的矩阵接近奇异而无法求逆的问题,采用广义逆矩阵的方法求多层径向基函数网络中各层的权重向量,并将这种方法引至多层径向基函数网络的遗传算法中。采用实函数逼近,混沌时间序列建模与预测等仿真实验对算法进行验证。结果表明,采用广义逆矩阵的方法要比正则最小二乘法在逼近精度上高1至2个数量级。
This paper introduces a new directional multilevel algorithm for solving N-body orN-point problems with highly oscillatory kernels. These systems often result from the boundary integral formulations o...
Two approaches for the efficient rational approximation of the Fermi-Dirac function are discussed: one uses the contour integral representation and conformal mapping, and the other is based on a versi...
This paper introduces a new sweeping preconditioner for the iterative solution of the variable coefficient Helmholtz equation in two and three dimensions. The algorithms follow the general structure o...

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