بدائل البحث:
maximization algorithm » optimization algorithms (توسيع البحث), classification algorithm (توسيع البحث)
features maximization » feature optimization (توسيع البحث), feature elimination (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
binary wave » binary image (توسيع البحث)
wave model » naive model (توسيع البحث), game model (توسيع البحث), base model (توسيع البحث)
maximization algorithm » optimization algorithms (توسيع البحث), classification algorithm (توسيع البحث)
features maximization » feature optimization (توسيع البحث), feature elimination (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
binary wave » binary image (توسيع البحث)
wave model » naive model (توسيع البحث), game model (توسيع البحث), base model (توسيع البحث)
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Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf
منشور في 2024"…A support vector machine (SVM) is attractive because binary classification can be represented as an optimization problem, in particular as a Quadratic Unconstrained Binary Optimization (QUBO) model, which, in turn, maps naturally to an Ising model, thereby making annealing—classical, quantum, and hybrid—an attractive approach to explore. …"
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2
MCLP_quantum_annealer_V0.5
منشور في 2025"…Theoretical and applied experiments are conducted using four solvers: QBSolv, D-Wave Hybrid binary quadratic model 2, D-Wave Advantage system 4.1, and Gurobi. …"
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Contextual Dynamic Pricing with Strategic Buyers
منشور في 2024"…The seller does not observe the buyer’s true feature, but a manipulated feature according to buyers’ strategic behavior. …"
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4
Supplementary Material 8
منشور في 2025"…</li><li><b>Naïve bayes (NB): </b> A probabilistic classifier based on Bayes' theorem, suitable for predicting resistance phenotypes based on genomic features.</li><li><b>Linear discriminant Analysis (LDA) is a statistica</b>l approach that maximizes class separability. …"
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Adaptive Inference for Change Points in High-Dimensional Data
منشور في 2021"…On the estimation front, we obtain the convergence rate of the maximizer of our test statistic standardized by sample size when there is one change-point in mean and <i>q</i> = 2, and propose to combine our tests with a wild binary segmentation algorithm to estimate the change-point number and locations when there are multiple change-points. …"