Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To address this challenge, we propose two novel semi-supervised clustering methods that incorporate prior knowledge in the form of pairwise cluster membership constraints. In particular, we project high-dimensional data onto a much red...

The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informative inference of continuous-basis fields, that is where the basis for the field is itself a continuous object and not representable in a finite manner; the tradeoff between accuracy of representation in terms of informati...

IONS AND METHODOLOGY Computer architecture’s heavy emphasis on simulation effectively discourages the research community from exploring other useful and possibly more informative modeling techniques. The few published papers using and proposing analytic models have not stimulated significant follow-up efforts. Stories abound of such papers receiving knee-jerk negative rejections from program co...

An interconnection network is usually modeled as a graph, in which vertices and edges correspond to processor and communication links, respectively. Connectivity is an important measurement for the fault tolerant in interconnection network. Two vertices is maximally local-connected if the maximum number of internally vertex-disjoint paths between them equals the minimum degree of these two vert...

No doubt that there is a great demand on digital era. Reaching millions of customers using internet encourages all companies regardless of their types to build their own websites and market their products, services and information through internet. In this paper, an enhanced framework is developed which can be used from different types of informative companies to build a successful website. The...

It is increasingly recognized that good reliability practice requires giving attention to the specification of joint distributions for failure times. If the marginal distributions are known then the problem of selecting a marginal distribution is equivalent to that of selecting a copula. In the competing risk situation, identification of the copula alone is important, for together with competin...

Fractal scale-free networks are empirically known to exhibit disassortative degree mixing. It is, however, not obvious whether a negative degree correlation between nearest neighbor nodes makes a scale-free network fractal. Here we examine the possibility that disassortativity in complex networks is the origin of fractality. To this end, maximally disassortative (MD) networks are prepared by re...

The paper addresses the problem of recovering a pseudoconvex function from the normal cones to its level sets that we call the convex level sets integration problem. An important application is the revealed preference problem. Our main result can be described as integrating a maximally cyclically pseudoconvex multivalued map that sends vectors or “bundles” of a Euclidean space to convex sets in...