Section Channel classification (Binary classification part): Weights obtained by the optimised classification algorithm. by Fabien Raphel (9421987)

Proposed Algorithm. by Hend Bayoumi (22693738)

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

Related Work Summary. by Hend Bayoumi (22693738)

Subjects:

Simulation parameters. by Hend Bayoumi (22693738)

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

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

Subjects:

An example of a type of texture of binary preferred/non-preferred ranges of raw vegetation index values type feature. by Elise Varaela Voltura (17592996)

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses by Meichen Liu (8168148)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

“…<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). …”

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

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

“…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. …”