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Algorithms

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  • Genetic Algorithms

Showing page 9 of 9.

  • JNano-math Icon
    JNano-math

    Common classes to perform mathematical operations

    0 weekly downloads
  • OpenAIL Icon
    OpenAIL

    [Open Artificial Intelligence Library]. This library main goal is to provide a tool box to those who want to use algorithm such as neural network or genetics Algorithm and all algorithms that are commonly within the Artificial Intelligence field.

    0 weekly downloads
  • ProximityForest Icon
    ProximityForest

    Efficient Approximate Nearest Neighbors for General Metric Spaces

    0 weekly downloads
  • Rating AnalyzerTask for iQser GIN Icon
    Rating AnalyzerTask for iQser GIN

    niPRO AnalyzerTask to calculate the rate popularity

    0 weekly downloads
  • Recursive Interpretation for XML Icon
    Recursive Interpretation for XML

    An interface for recursive descent XML Parsing

    0 weekly downloads
  • TreeLayout Icon
    TreeLayout

    Efficiently create compact, highly customizable tree layouts - Based on Walker's algorithm with enhancements suggested by Buchheim, Jünger, and Leipert the software builds tree layouts in linear time. I.e. even trees with many nodes are built fast. NOTICE: The project is moved to https://treelayout.googlecode.com/

    0 weekly downloads
  • WALA Icon
    WALA

    The T. J. Watson Libraries for Analysis (WALA) provide program analysis capabilities for Java bytecode and related languages. The WALA libraries constitute an open-source release of parts of IBM Research's DOMO analysis infrastructure.

    0 weekly downloads
  • cl-string-match Icon
    cl-string-match

    String matching algorithms implementation for Lisp

    0 weekly downloads
  • p-euler Icon
    p-euler

    problem solving practicing from projecteuler.net

    0 weekly downloads
  • pegasus Icon
    pegasus

    Semantic query optimization (SQO) is the process of finding equivalent rewritings of an input query given constraints that hold in a database instance. We present a Chase & Backchase (C&B) algorithm strategy that generalizes and improves on well-known methods in the field. The implementation of our approach, the pegasus system, outperforms existing C&B systems an average by two orders of magnitude. This gain in performance is due to a combination of novel methods that lower the complexity in practical situations significantly.

    0 weekly downloads
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