Showing 1 - 18 results of 18 for search '(( elements per algorithm ) OR ((( element scheduling algorithm ) OR ( neural coding algorithm ))))', query time: 0.12s Refine Results
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    GENETIC SCHEDULING OF TASK GRAPHS by Benten, M. S.

    Published 2020
    “…A genetic algorithm for scheduling computational task graphs is presented. …”
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    article
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    A Parallel Neural Networks Algorithm for the Clique Partitioning Problem by Harmanani, Haidar M.

    Published 2002
    “…The clique partitioning problem has important applications in many areas including VLSI design automation, scheduling, and resources allocation. In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
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    article
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    Correlation Clustering with Overlaps by Fakhereldine, Amin

    Published 2020
    “…We present a heuristic algorithm and a semi-exact algorithm for the Multi-Parameterized Cluster Editing with Vertex Splitting problem. …”
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    masterThesis
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    Multidimensional Gains for Stochastic Approximation by Saab, Samer S.

    Published 2019
    “…The proposed algorithms here aim for per-iteration minimization of the mean square estimate error. …”
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    On the complexity of multi-parameterized cluster editing by Abu-Khzam, Faisal

    Published 2017
    “…In other words, Cluster Editing can be solved efficiently when the number of false positives/negatives per single data element is expected to be small compared to the minimum cluster size. …”
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    article
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    Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

    Published 2024
    “…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”
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    Developing an online hate classifier for multiple social media platforms by Joni Salminen (7434770)

    Published 2020
    “…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”