to a particular set of `observed' phases; that is, the function minimized is V whereas we should ideally seek to minimize A I h We can approach this ideal with Diamond's method by using a new map for each cycle, the coefficients of which are or Nonetheless, this i

A novel scheme for the detection of object boundaries is presented. The technique is based on active contours evolving in time according to intrinsic geometric measures of the image. The evolving contours naturally split and merge, allowing the simultaneous detection of several objects and both

managed fashion, but without sacrificing either performance or functionality. This is achieved by providing an idealized virtual machine abstraction to which operating systems such as Linux, BSD and Windows XP, can be ported with minimal effort. Our design is targeted at hosting up to 100 virtual machine

task. We claim that the increased efficiency is due to (1) employing a principled method of crossover of different topologies, (2) protecting structural innovation using speciation, and (3) incrementally growing from minimal structure. We test this claim through a series of ablation studies

by the principle of minimizing the Stein Unbiased Estimate of Risk (Sure) for threshold estimates. The computational effort of the overall procedure is order N log(N) as a function of the sample size N. SureShrink is smoothness-adaptive: if the unknown function contains jumps, the reconstruction (essentially) does

gains from simultaneous multithreading can be achieved without extensive changes to a conventional wide-issue superscalar, either in hardware structures or sizes. We present an architecture for simultaneous multithreading that achieves three goals: (1) it minimizes the architectural impact

We consider scheduling jobs online to minimize the objective i∈[n] wig(Ci − ri), where wi is the weight of job i, ri is its release time, Ci is its completion time and g is any non-decreasing convex function. Previously, it was known that the clairvoyant algorithm Highest-Density-First (HDF) is (2

An improved method of crystallographic structure refinement, especially suitabte for large molecules, is described. It is based on simultaneous minimization of a realistic potential-energy function and a crystallographic residual. The method has already proved its worth in the final stages

Consider the problem of finding a root of the multivariate gradient equation that arises in function minimization. When only noisy measurements of the function are available, a stochastic approximation (SA) algorithm of the general Kiefer-Wolfowitz type is appropriate for estimating the root

must be minimized. These two objectives cannot be satisfied simultaneously by employing routing algorithms proposed in previous work. In this article we present a new power-aware routing protocol to satisfy these two constraints simultaneously; we also compare the performance of different types