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augmentations » augmentation (Expand Search), argumentation (Expand Search), alimentation (Expand Search)
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augmentations » augmentation (Expand Search), argumentation (Expand Search), alimentation (Expand Search)
recommendation » recommendations (Expand Search)
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Web Based Online Hybrid Teaching Method of Network Music Course
Published 2022Subjects: Get full text
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”
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Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm?
Published 2021“…The resulting model achieves an 89% predictive accuracy using historical data. A unique aspect of the model is the incorporation of self-competence, where the model defers when it cannot reasonably make a recommendation. …”
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A Recommended Replacement Algorithm for the Scalable Asynchronous Cache Consistency Scheme
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K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation
Published 2022“…This paper introduces K Nearest Neighbor OveRsampling (KNNOR) Algorithm — a novel data augmentation technique that considers the distribution of data and takes into account the k nearest neighbors while generating artificial data points. …”
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Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System
Published 2021“…We research and test the design of the right neural networks that achieves our goal. A modern algorithm was improvised for this reason. For our proposed recommendation system, a database program was created to store data and include details in the analysis of course learning outcomes. …”
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Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem
Published 2016“…This research note describes Response-Based Unit Segmentation (REBUS), a “latent class detection” technique used in partial least squares–structural equation modeling (PLS-SEM) to examine data heterogeneity. …”
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Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units
Published 2019Subjects: Get full text
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
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Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations
Published 2022“…The best available recommendation algorithms are based on using the observed preference information among collaborating entities. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …”
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A comparison of data mapping algorithms for parallel iterative PDE solvers
Published 1995“…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …”
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Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021“…We show how our algorithm supports the definition of a budget for alignment computation and also augment it with strategies for meta-heuristic optimization and pruning of the search space. …”
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KNNOR: An oversampling technique for imbalanced datasets
Published 2021“…The proposed technique called K-Nearest Neighbor OveRsampling approach (KNNOR) performs a three step process to identify the critical and safe areas for augmentation and generate synthetic data points of the minority class. …”
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A multi-pretraining U-Net architecture for semantic segmentation
Published 2025“…Particularly, we present a novel non-sequential multi-pretraining U-Net architecture and demonstrate that employing a number of persistent parallel models can boost the effectiveness of the segmentation procedures. The proposed approach makes advantage of data augmentation to generate newly synthesized images, which are subsequently processed using a watershed mask. …”