Showing 1 - 18 results of 18 for search '(((( elements graph algorithms ) OR ( elements upon 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
    “…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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    Properties of Unique Degree Sequences of 3-Uniform Hypergraphs by Tarsissi, Lama

    Published 2021
    “…A well known result of Erdös and Gallai (1960) shows that the same problem related to graphs can be solved in polynomial time. So, it becomes relevant to detect classes of uniform hypergraphs that are reconstructible in polynomial time. …”
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    Correlation Clustering with Overlaps by Fakhereldine, Amin

    Published 2020
    “…The Cluster Editing problem asks for transforming a given graph into a disjoint union of cliques by applying a minimal number of edge-editing operations. …”
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    masterThesis
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    On the complexity of multi-parameterized cluster editing by Abu-Khzam, Faisal

    Published 2017
    “…The Cluster Editing problem seeks a transformation of a given undirected graph into a disjoint union of cliques via a minimum number of edge additions or deletions. …”
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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). …”