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Improved search-tree algorithms for the cluster edit problem. (c2011)
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Scalable parallel algorithms for dynamic programming on tree decomposition. (c2017)
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A parallel search tree algorithm for vertex cover on graphical processing units. (c2013)
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4
A decentralized load balancing strategy for parallel search-three optimization. (c2010)
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5
The buffered work-pool approach for search-tree based optimization algorithms
Published 2017“…This new trend has been motivated by hardness of approximation results that appeared in the last decade, and has taken a great boost by the emergence of parameterized complexity theory. Exact algorithms often follow the classical search-tree based recursive backtracking strategy. …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…The paper proposes a concurrent job scheduling algorithm in a multi-energy data source environment using Apache Spark. …”
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Predict Student Success and Performance factors by analyzing educational data using data mining techniques
Published 2022“…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …”
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Properties of simulated annealing and genetic algorithms for mapping data to multicomputers
Published 1997“…We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorithms (GA) for mapping data to multicomputers. …”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…Then, it searches for population discriminative motifs or differentiable sequence of SNPs, by implementing Probabilistic Suffix Trees data structures. We initially tested the efficiency and performance of our method on several simulated datasets and then applied it on a real genomic data that has different populations from the Middle East and North Africa (MENA) region. …”
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masterThesis -
11
Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
Published 2022“…Extracted vegetation indices were evaluated on three ML algorithms, namely, random forest (RF), k-nearest neighbour (K-NN), and k dimensional-tree (KD-Tree). …”
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019“…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…The data forecasting horizon used was a 24-h window in steps of 30 min. …”
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
Published 2019“…The reported accuracy dramatically outperforms the previous algorithms, including gradient tree boosting (GTB), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and linear discriminant analysis (LDA). …”
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Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose
Published 2020“…These electronic instruments rely on Machine Learning (ML) algorithms for recognizing the sensed odors. The effect of long-term drift influences the performance of ML algorithms and the models those are trained on drift free data fail to perform on the drifted data. …”
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Efficient XML Structural Similarity Detection using Sub-tree Commonalities
Published 2007“…Developing efficient techniques for comparing XML-based documents becomes essential in the database and information retrieval communities. Various algorithms for comparing hierarchically structured data, e.g. …”
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conferenceObject -
17
Sentiment visualization of correlation of loneliness mapped through social intelligence analysis
Published 2024“…In the second part, interactive visualizations are developed to present the findings in an engaging and intuitive manner. Techniques such as tree maps and radar plots are utilized to transform the analyzed data into visually appealing representations.…”
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Defining quantitative rules for identifying influential researchers: Insights from mathematics domain
Published 2024“…The rules were developed for each parameter category using the Decision Tree Algorithm, which achieved an average accuracy of 70 to 75 percent for identifying awardees in mathematics domains. …”
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A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics
Published 2011“…XML similarity evaluation has become a central issue in the database and information communities, its applications ranging over document clustering, version control, data integration and ranked retrieval. Various algorithms for comparing hierarchically structured data, XML documents in particular, have been proposed in the literature. …”
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