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    MASCOTS
    2008
    112views Modeling And Simulation» more  MASCOTS 2008»
    Finding Good Configurations in High-Dimensional Spaces: Doing More with Less
    15 years 2 months ago
    Finding Good Configurations in High-Dimensional Spaces: Doing More with Less
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    Manually tuning tens to hundreds of configuration parameters in a complex software system like a database or an application server is an arduous task. Recent work has looked into ...
    Risi Thonangi, Vamsidhar Thummala, Shivnath Babu
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    103
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    IJCAI
    2007
    162views Artificial Intelligence» more  IJCAI 2007»
    Improving Anytime Point-Based Value Iteration Using Principled Point Selections
    15 years 2 months ago
    Improving Anytime Point-Based Value Iteration Using Principled Point Selections
    Download  ai.stanford.edu
    Planning in partially-observable dynamical systems (such as POMDPs and PSRs) is a computationally challenging task. Popular approximation techniques that have proved successful ar...
    Michael R. James, Michael E. Samples, Dmitri A. Do...
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    IPCO
    2007
    143views Optimization» more  IPCO 2007»
    On the Exact Separation of Mixed Integer Knapsack Cuts
    15 years 2 months ago
    On the Exact Separation of Mixed Integer Knapsack Cuts
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    During the last decades, much research has been conducted deriving classes of valid inequalities for single-row mixed integer programming polyhedrons. However, no such class has ha...
    Ricardo Fukasawa, Marcos Goycoolea
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    96
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    IQ
    2007
    96views Information Technology» more  IQ 2007»
    Quality Of Data, Information And Knowledge In Technology Foresight Processes
    15 years 2 months ago
    Quality Of Data, Information And Knowledge In Technology Foresight Processes
    Download  mitiq.mit.edu
    : Futures research means observation and understanding of today’s operational environment as well as identification and positioning of future opportunities. Lots of technology fo...
    Helinä Melkas, Tuomo Uotila
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    112
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    SDM
    2008
    SIAM
    176views Data Mining» more  SDM 2008»
    A General Model for Multiple View Unsupervised Learning
    15 years 2 months ago
    A General Model for Multiple View Unsupervised Learning
    Download  www.cs.binghamton.edu
    Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
    Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
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