In this paper we focus our topic on linear separability of two data sets in feature space, including finite and infinite data sets. We first develop a method to construct a mapping that maps original data set into a high dimensional feature space, on which inner product is defined by a dot product kernel. Our method can also be applied to the Gaussian kernels. Via this mapping, structure of fea...

We present a genie based outer bound for the sum rate of memoryless interference channels. When applied to the scalar Gaussian interference channel, this bound recovers all known capacity results.

The Essential Ideas Let us begin by congratulating Danaher and Smith (2011) on an excellent contribution that serves as a lucid introduction to copula modeling, as well as providing a sensible Bayesian approach for its application to both continuous and discrete data. The essential concept we take away is that modeling dependence in multivariate data is facilitated by transforming the marginal ...

A first-order autoregressive process with inverse gaussian marginals is introduced. The innovation distributions are obtained under certain special cases. The unknown parameters are estimated using different methods and these estimators are shown to be consistent and asymptotically normal. The behavior of the estimators for small samples is studied through simulation experiments. On Sums of Tri...

This paper presents a low-area nite eld divider using dual basis representation. This divider is based on the division algorithm of solving Discrete Wiener-Hopf Equation using Gauss-Jordan elimination method. The hardware complexity of the matrix generation part has been reduced dramatically form O(m) to O(m). When it is used as a building block for a large system, this divider can achieve more...

A vertex reconstruction algorithm was developed based on the Gaussian-sum filter (GSF) and implemented in the framework of the CMS reconstruction program. While linear least-square estimators are optimal in case all observation errors are Gaussian distributed, the GSF offers a better treatment of non-Gaussian distributions of track parameter errors when these are modelled by Gaussian mixtures. ...

Recently, it was shown that a binary linear code can be associated to a binomial ideal given as the sum of a toric ideal and a non-prime ideal. Since then two different generalizations have been provided which coincide for the binary case. In this paper, we establish some connections between the two approaches. In particular, we show that the corresponding code ideals are related by elimination...

We consider standard Λ-coalescents (or coalescents with multiple collisions) with a non-trivial “Kingman part”. Equivalently, the driving measure Λ has an atom at 0; Λ({0}) = c > 0. It is known that all such coalescents come down from infinity. Moreover, the number of blocks Nt is asymptotic to v(t) = 2/(ct) as t → 0. In the present paper we investigate the second-order asymptotics of Nt in the...

We present the path-sum formulation for exact statistical inference of marginals on Gaussian graphical models of arbitrary topology. The path-sum formulation gives the covariance between each pair of variables as a branched continued fraction of finite depth and breadth. Our method originates from the closed-form resummation of infinite families of terms of the walk-sum representation of the co...

We consider electromagnetic interrogation problems for complex materials involving distributions of polarization mechanisms and also distributions for the parameters in these mechanisms. A theoretical and computational framework for such problems is given. Computational results for specific problems with multiple Debye mechanisms are given in the case of discrete, uniform, log-normal, and log-b...