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processes optimization » process optimization (Expand Search), process optimisation (Expand Search), property optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
based processes » care processes (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
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processes optimization » process optimization (Expand Search), process optimisation (Expand Search), property optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
based processes » care processes (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary i » binary _ (Expand Search)
i design » _ design (Expand Search), a design (Expand Search), co design (Expand Search)
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Contextual Dynamic Pricing with Strategic Buyers
Published 2024“…This underscores the rate optimality of our policy. Importantly, our policy is not a mere amalgamation of existing dynamic pricing policies and strategic behavior handling algorithms. …”
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122
Thesis-RAMIS-Figs_Slides
Published 2024“…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”
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Seed mix selection model
Published 2022“…Classic genetic algorithms consider a population of chromosomes and apply principles of natural selection (selection, mutation, and crossover processes) to generate optimal solutions. …”
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Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx
Published 2025“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”
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Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx
Published 2020“…In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. …”
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130
DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. …”
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131
Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. …”
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132
Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction
Published 2020“…We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.…”
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133
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…Details on the data sourcing process, prompt engineering strategies for large language model (LLM)-based extraction, and validation protocols are provided in the Supplementary Information section.…”