Motivation (1) Distributed wireless networks arise in various forms. (2) Knowledge of the link gain matrix can be highly valuable in planning and using large-scale distributed wireless networks. (3) If the number N of radio nodes is large, measuring N(N1)/2 node-to-node link gains can be prohibitive.  This motivates us to devise a methodology that measures a fraction of the links and accuratel...

Integration of language constraints into a large vocabulary speech recognition system often leads to prohibitive complexity. We propose to factor the constraints into two components. The first is characterized by a covering grammar which is small and easily integrated into existing speech recognizers. The recognized string is then decoded by means of an efficient language post-processor in whic...

Discrete-velocity approximations represent a popular way for computing the Boltzmann collision operator. The direct numerical evaluation of such methods involve a prohibitive cost, typically O(N) where d is the dimension of the velocity space. In this paper, following the ideas introduced in [27, 28], we derive fast summation techniques for the evaluation of discrete-velocity schemes which perm...

The performance of a computer system is aaected by the characteristics of its various hardware and software subsytems. Hardware and software characterisation give the ability to change machine and programs parameters and observe their eeects on the performance of the system without changing the existing hardware which can be time consuming and cost prohibitive. This report provides a survey of ...

Integral equation techniques are often used to extract models of integrated circuit structures. This extraction involves solving a dense system of linear equations, and using direct solution methods is prohibitive for large problems. In this paper, we present IES (pronounced \ice cube"), a fast Integral Equation Solver for three-dimensional problems with arbitrary kernels. Extraction methods ba...

Tensor decompositions are a valuable tool in data analysis, but the computational cost of standard tensor algorithms quickly becomes prohibitive, especially when considering large and time-evolving data sets such as those found in signal processing applications. In this work multilinear PCA, a common tensor analysis technique, will be modified to enable the processing of large scale tensorial t...

A prohibitive barrier faced by elliptic curve users is the difficulty of computing the curves’ cardinalities. Despite recent theoretical breakthroughs, point counting still remains very cumbersome and intensively time consuming. In this paper we show that point counting can be avoided at the cost of a protocol slow-down. This slow-down factor is quite important (typically ∼= 500) but proves tha...

24 Changes are needed to make significant improvements to operational availability and must be considered as early as possible during the design cycle; however, after initial system development, design changes are typically cost-prohibitive. The Department of Defense needs to ensure maintenance and supportability are considered during all phases of the system development cycle, particularly dur...

This has much in common with traditional work in statistics and machine learning. However, there are important new issues which arise because of the sheer size of the data. One of the important problem in data mining is the Classificationrule learning which involves finding rules that partition given data into predefined classes. In the data mining domain where millions of records and a large n...

Consider the following outlier detection problem: suppose you are given an unlabeled data set and make the assumptions that one particular class is well-represented but you have no prior knowledge on how many outliers it contains. This scenario can arise in a variety of real world applications such as detecting intrusions in a network or spotting malignant tumors in medical images. Although con...