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    MONET
    2008
    150views more  MONET 2008»
    A Multi-radio 802.11 Mesh Network Architecture
    13 years 8 months ago
    A Multi-radio 802.11 Mesh Network Architecture
    Download  moment.cs.ucsb.edu
    Routers equipped with multiple 802.11 radios can alleviate capacity problems in wireless mesh networks. However, a practical, complete system architecture that can realize the bene...
    Krishna N. Ramachandran, Irfan Sheriff, Elizabeth ...
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    KAIS
    2006
    110views more  KAIS 2006»
    Multi-step density-based clustering
    13 years 8 months ago
    Multi-step density-based clustering
    Download  www.dbs.informatik.uni-muenchen.de
    Abstract. Data mining in large databases of complex objects from scientific, engineering or multimedia applications is getting more and more important. In many areas, complex dista...
    Stefan Brecheisen, Hans-Peter Kriegel, Martin Pfei...
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    ML
    2006
    ACM
    99views Machine Learning» more  ML 2006»
    Universal parameter optimisation in games based on SPSA
    13 years 8 months ago
    Universal parameter optimisation in games based on SPSA
    Download  www.jhuapl.edu
    Most game programs have a large number of parameters that are crucial for their performance. While tuning these parameters by hand is rather difficult, efficient and easy to use ge...
    Levente Kocsis, Csaba Szepesvári
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    PAMI
    2008
    190views more  PAMI 2008»
    Scene Classification Using a Hybrid Generative/Discriminative Approach
    13 years 8 months ago
    Scene Classification Using a Hybrid Generative/Discriminative Approach
    Download  cvcl.mit.edu
    We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail we are given a set ...
    Anna Bosch, Andrew Zisserman, Xavier Muñoz
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    PAMI
    2008
    161views more  PAMI 2008»
    TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
    13 years 8 months ago
    TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
    Download  people.ece.cornell.edu
    The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
    Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
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