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    STOC
    2009
    ACM
    96views Algorithms» more  STOC 2009»
    MaxMin allocation via degree lower-bounded arborescences
    14 years 8 months ago
    MaxMin allocation via degree lower-bounded arborescences
    Download  www.cs.washington.edu
    We consider the problem of MaxMin allocation of indivisible goods. There are m items to be distributed among n players. Each player i has a nonnegative valuation pij for an item j...
    MohammadHossein Bateni, Moses Charikar, Venkatesan...
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    STOC
    2009
    ACM
    160views Algorithms» more  STOC 2009»
    CSP gaps and reductions in the lasserre hierarchy
    14 years 8 months ago
    CSP gaps and reductions in the lasserre hierarchy
    Download  eccc.hpi-web.de
    We study integrality gaps for SDP relaxations of constraint satisfaction problems, in the hierarchy of SDPs defined by Lasserre. Schoenebeck [25] recently showed the first integra...
    Madhur Tulsiani
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    ALMOB
    2006
    80views more  ALMOB 2006»
    Effective p-value computations using Finite Markov Chain Imbedding (FMCI): application to local score and to pattern statistics
    13 years 7 months ago
    Effective p-value computations using Finite Markov Chain Imbedding (FMCI): application to local score and to pattern statistics
    Download  www.almob.org
    The technique of Finite Markov Chain Imbedding (FMCI) is a classical approach to complex combinatorial problems related to sequences. In order to get efficient algorithms, it is k...
    Grégory Nuel
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    CORR
    2008
    Springer
    132views Education» more  CORR 2008»
    Dynamic Rate Allocation in Fading Multiple-access Channels
    13 years 7 months ago
    Dynamic Rate Allocation in Fading Multiple-access Channels
    Download  web.mit.edu
    We consider the problem of rate allocation in a fading Gaussian multiple-access channel (MAC) with fixed transmission powers. Our goal is to maximize a general concave utility func...
    Ali ParandehGheibi, Atilla Eryilmaz, Asuman E. Ozd...
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    CVPR
    2005
    IEEE
    206views Computer Vision» more  CVPR 2005»
    Kernel-Based Bayesian Filtering for Object Tracking
    14 years 9 months ago
    Kernel-Based Bayesian Filtering for Object Tracking
    Download  www.caip.rutgers.edu
    Particle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, the algorithm is based on a Monte Ca...
    Bohyung Han, Ying Zhu, Dorin Comaniciu, Larry S. D...
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