Search alternatives:
derived optimization » driven optimization (Expand Search), required optimization (Expand Search), guided optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
data derived » data driven (Expand Search)
image design » images designed (Expand Search), simple design (Expand Search), space design (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
derived optimization » driven optimization (Expand Search), required optimization (Expand Search), guided optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
data derived » data driven (Expand Search)
image design » images designed (Expand Search), simple design (Expand Search), space design (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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<i>hi</i>PRS algorithm process flow.
Published 2023“…<b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …”
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Sample image for illustration.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Quadratic polynomial in 2D image plane.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes
Published 2022“…Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …”
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