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    CSDA
    2007
    100views more  CSDA 2007»
    Convergence of random k-nearest-neighbour imputation
    13 years 7 months ago
    Convergence of random k-nearest-neighbour imputation
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    Random k-nearest-neighbour (RKNN) imputation is an established algorithm for filling in missing values in data sets. Assume that data are missing in a random way, so that missing...
    Fredrik A. Dahl
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    TIT
    2008
    103views more  TIT 2008»
    Fast Distributed Algorithms for Computing Separable Functions
    13 years 7 months ago
    Fast Distributed Algorithms for Computing Separable Functions
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    The problem of computing functions of values at the nodes in a network in a fully distributed manner, where nodes do not have unique identities and make decisions based only on loc...
    Damon Mosk-Aoyama, Devavrat Shah
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    TCS
    2010
    133views Theoretical Computer Science» more  TCS 2010»
    Maximum likelihood analysis of algorithms and data structures
    13 years 6 months ago
    Maximum likelihood analysis of algorithms and data structures
    Download  wwwagak.informatik.uni-kl.de
    We present a new approach for an average-case analysis of algorithms and data structures that supports a non-uniform distribution of the inputs and is based on the maximum likelih...
    Ulrich Laube, Markus E. Nebel
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    GECCO
    2005
    Springer
    126views Optimization» more  GECCO 2005»
    Not all linear functions are equally difficult for the compact genetic algorithm
    14 years 1 months ago
    Not all linear functions are equally difficult for the compact genetic algorithm
    Download  www.cs.bham.ac.uk
    Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
    Stefan Droste
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    SODA
    2008
    ACM
    110views Algorithms» more  SODA 2008»
    Why simple hash functions work: exploiting the entropy in a data stream
    13 years 9 months ago
    Why simple hash functions work: exploiting the entropy in a data stream
    Download  www.eecs.harvard.edu
    Hashing is fundamental to many algorithms and data structures widely used in practice. For theoretical analysis of hashing, there have been two main approaches. First, one can ass...
    Michael Mitzenmacher, Salil P. Vadhan
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