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This paper ties the line of work on algorithms that find an O(??(log n))-approximation to the SPARSEST CUT together with the line of work on algorithms that run in subquadratic time by using only single-commodity flows. We present an algorithm that simultaneously achieves both goals, finding an O(??(log (n)/??))-approximation using O(n?? logO(1) n) max-flows. The core of the algorithm is a stronger,...
In estimating a finite length signal vector that has been corrupted by additive stationary noise, a variety of statistical estimation forms exist. These forms may be based on least squares, maximum likelihood, empirical Bayes, or minimax principles. Often, the actions of such forms are not readily evident, in contrast to those of frequency domains forms used in engineering and based on an infinite...
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