Search alternatives:
common optimization » codon optimization (Expand Search), carbon optimization (Expand Search), cosmic optimization (Expand Search)
across optimization » cost optimization (Expand Search), stress optimization (Expand Search), process optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
common optimization » codon optimization (Expand Search), carbon optimization (Expand Search), cosmic optimization (Expand Search)
across optimization » cost optimization (Expand Search), stress optimization (Expand Search), process optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025“…The algorithm was applied to aqueous, binary mixture systems composed of 37 common biochemical substances such as amino acids, organic acids, and sugars. …”
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Generalized Tensor Decomposition With Features on Multiple Modes
Published 2021“…An efficient alternating optimization algorithm with provable spectral initialization is further developed. …”
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Flow diagram of the proposed model.
Published 2025“…Local Interpretable Model-agnostic Explanations (LIME) were applied to improve interpretability. Across all algorithm models, LR–ABC hybrids outperformed their baseline models (e.g., Random Forest: 85.2% → 91.36% accuracy). …”
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Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level
Published 2021“…Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”
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Thesis-RAMIS-Figs_Slides
Published 2024“…In this direction, the option of estimating the statistics of the model directly from the training image (performing a refined pattern search instead of simulating data) is a very promising.<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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DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf
Published 2022“…Improvement of the classification rate is expected with optimized model parameters and algorithms as well as with a larger spectral data base for training.…”
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Event-driven data flow processing.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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MCLP_quantum_annealer_V0.5
Published 2025“…Currently, classical high-performance and parallel spatial computing architectures are commonly employed to solve geospatial optimization problems. …”
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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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Confusion matrix.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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Parameter settings.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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Dynamic resource allocation process.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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Bayesian sequential design for sensitivity experiments with hybrid responses
Published 2023“…<p>In experimental design, a common problem seen in practice is when the result includes one binary response and multiple continuous responses. …”