5,395 research outputs found

    An interior point algorithm for minimum sum-of-squares clustering

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    Copyright @ 2000 SIAM PublicationsAn exact algorithm is proposed for minimum sum-of-squares nonhierarchical clustering, i.e., for partitioning a given set of points from a Euclidean m-space into a given number of clusters in order to minimize the sum of squared distances from all points to the centroid of the cluster to which they belong. This problem is expressed as a constrained hyperbolic program in 0-1 variables. The resolution method combines an interior point algorithm, i.e., a weighted analytic center column generation method, with branch-and-bound. The auxiliary problem of determining the entering column (i.e., the oracle) is an unconstrained hyperbolic program in 0-1 variables with a quadratic numerator and linear denominator. It is solved through a sequence of unconstrained quadratic programs in 0-1 variables. To accelerate resolution, variable neighborhood search heuristics are used both to get a good initial solution and to solve quickly the auxiliary problem as long as global optimality is not reached. Estimated bounds for the dual variables are deduced from the heuristic solution and used in the resolution process as a trust region. Proved minimum sum-of-squares partitions are determined for the rst time for several fairly large data sets from the literature, including Fisher's 150 iris.This research was supported by the Fonds National de la Recherche Scientifique Suisse, NSERC-Canada, and FCAR-Quebec

    A multiple-cut analytic center cutting plane method for semidefinite feasibility problems

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    10.1137/S1052623400370503SIAM Journal on Optimization1241126-114

    Solving nonlinear multicommodity flow problems by the analytic center cutting plane method

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    The paper deals with nonlinear multicommodity flow problems with convex costs. A decomposition method is proposed to solve them. The approach applies a potential reduction algorithm to solve the master problem approximately and a column generation technique to define a sequence of primal linear programming problems. Each subproblem consists of finding a minimum cost flow between an origin and a destination node in an uncapacited network. It is thus formulated as a shortest path problem and solved with Dijkstra's d-heap algorithm. An implementation is described that takes full advantage of the supersparsity of the network in the linear algebra operations. Computational results show the efficiency of this approach on well-known nondifferentiable problems and also large scale randomly generated problems (up to 1000 arcs and 5000 commodities

    Rounding Algorithms for a Geometric Embedding of Minimum Multiway Cut

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    The multiway-cut problem is, given a weighted graph and k >= 2 terminal nodes, to find a minimum-weight set of edges whose removal separates all the terminals. The problem is NP-hard, and even NP-hard to approximate within 1+delta for some small delta > 0. Calinescu, Karloff, and Rabani (1998) gave an algorithm with performance guarantee 3/2-1/k, based on a geometric relaxation of the problem. In this paper, we give improved randomized rounding schemes for their relaxation, yielding a 12/11-approximation algorithm for k=3 and a 1.3438-approximation algorithm in general. Our approach hinges on the observation that the problem of designing a randomized rounding scheme for a geometric relaxation is itself a linear programming problem. The paper explores computational solutions to this problem, and gives a proof that for a general class of geometric relaxations, there are always randomized rounding schemes that match the integrality gap.Comment: Conference version in ACM Symposium on Theory of Computing (1999). To appear in Mathematics of Operations Researc

    The Atacama Cosmology Telescope: A Measurement of the 600< ell <8000 Cosmic Microwave Background Power Spectrum at 148 GHz

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    We present a measurement of the angular power spectrum of the cosmic microwave background (CMB) radiation observed at 148 GHz. The measurement uses maps with 1.4' angular resolution made with data from the Atacama Cosmology Telescope (ACT). The observations cover 228 square degrees of the southern sky, in a 4.2-degree-wide strip centered on declination 53 degrees South. The CMB at arcminute angular scales is particularly sensitive to the Silk damping scale, to the Sunyaev-Zel'dovich (SZ) effect from galaxy clusters, and to emission by radio sources and dusty galaxies. After masking the 108 brightest point sources in our maps, we estimate the power spectrum between 600 < \ell < 8000 using the adaptive multi-taper method to minimize spectral leakage and maximize use of the full data set. Our absolute calibration is based on observations of Uranus. To verify the calibration and test the fidelity of our map at large angular scales, we cross-correlate the ACT map to the WMAP map and recover the WMAP power spectrum from 250 < ell < 1150. The power beyond the Silk damping tail of the CMB is consistent with models of the emission from point sources. We quantify the contribution of SZ clusters to the power spectrum by fitting to a model normalized at sigma8 = 0.8. We constrain the model's amplitude ASZ < 1.63 (95% CL). If interpreted as a measurement of sigma8, this implies sigma8^SZ < 0.86 (95% CL) given our SZ model. A fit of ACT and WMAP five-year data jointly to a 6-parameter LCDM model plus terms for point sources and the SZ effect is consistent with these results.Comment: 15 pages, 8 figures. Accepted for publication in Ap
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