Proposed Algorithm. حسب Hend Bayoumi (22693738)

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CDF of task latency, approximated as the inverse of the achieved computation rate. حسب Hend Bayoumi (22693738)

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Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

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Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30. حسب Hend Bayoumi (22693738)

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Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30. حسب Hend Bayoumi (22693738)

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Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification حسب Vaibhavi Patel (19843282)

Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. حسب Tristan Mary-Huard (3864)

An Example of a WPT-MEC Network. حسب Hend Bayoumi (22693738)

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Related Work Summary. حسب Hend Bayoumi (22693738)

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Simulation parameters. حسب Hend Bayoumi (22693738)

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Training losses for N = 10. حسب Hend Bayoumi (22693738)

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Performance Comparison of State-of-the-Art WPT-MEC Offloading Methods. حسب Hend Bayoumi (22693738)

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The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames. حسب Hend Bayoumi (22693738)

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Normalized computation rate for N = 10. حسب Hend Bayoumi (22693738)

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Comparison between Bisection and Newton-Raphson in terms of (A) total time consumed, and (B) maximum computation rate. حسب Hend Bayoumi (22693738)

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Summary of Notations Used in this paper. حسب Hend Bayoumi (22693738)

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Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes حسب Yu Y. (3096192)

"…Introduction: Increasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. …"

Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods حسب Jiacong Du (12035845)

"…Building on existing work, we (i) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (ii) incorporate adaptive shrinkage penalties, (iii) compare these methods through simulation, and (iv) develop an R package <i>miselect</i>. …"