It is well known that conditional indepen­ dence can be used to factorize a joint prob­ ability into a multiplication of conditional probabilities. This paper proposes a con­ structive definition of intercausal indepen­ dence, which can be used to further factorize a conditional probability. An inference algo­ rithm is developed, which makes use of both conditional independence and intercausal ...

This paper explores the role of independence of causal influence (ICI) in Bayesian network inference. ICI allows one to factorize a con­ ditional probability table into smaller pieces. We describe a method for exploiting the fac­ torization in clique tree propagation (CTP) the state-of-the-art exact inference algo­ rithm for Bayesian networks. We also present empirical results showing that the ...

Given a set of n points and hyperrectangles in d dimensional space the batched range searching problem is to determine which points each hyperrectangle contains We present two parallel algorithms for this problem on a p n pn mesh connected paral lel computer one average case e cient algorithm based on cell division and one worst case e cient divide and conquer algo rithm Besides the asymptotic ...

Location estimation of mobile phones has received considerable interest in the eld of wireless communications In this pa per a simple and e cient positioning algo rithm using received signal strength measure ments obtained from at least three base stations are developed Our proposed method is based on solving a nonconvex constrained weighted least squares problem Simulation results show that th...

Localized eigenfunctions in the two-dimensional spectral problem containing a small parameter with higher derivatives are constructed on expected solution form. Localization this context means that exponentially decays both direc-tions starting from "weakest" point or line. The constructions based algo-rithm introduced by V.P. Maslov. A modification of algorithm for thin shell theory problems i...

This paper presents a fast and effective electromagnetic reconstruction algorithm with phaseless data under weak scattering conditions. The proposed algorithm is based on the phaseless data multiplicative regularized contrast sources inversion method (PDMRCSI). We recast the weak scattering problem as an optimization problem in terms of the undetermined contrast and contrast sources. Using the ...

We present a novel EM algorithm for model-based image segmentation which incorporates efficient and economical spatial constrains among pixels via a Markov random field model. We adopt a generative model in which the unobserved class labels of neighboring pixels in the image are assumed to be generated by prior distributions with similar parameters. We derive a penalized log-likelihood optimiza...

Presented here is a generalization of the implicit enumeration algorithm that can be applied when the objec-tive function is being maximized and can be rewritten as the difference of two non-decreasing functions. Also developed is a computational algorithm, named linear speedup, to use whatever explicit linear constraints are present to speedup the search for a solution. The method is easy to u...

Full perspective mappings between D objects and D images are more complicated than weak perspective mappings which consider only rotation translation and scaling Therefore in D model based robot navigation it is important to understand how and when full perspective must be taken into account In this paper we use a probabilistic combinatorial op timization algorithm to search for an optimal matc...