Search alternatives:
from optimization » fox optimization (Expand Search), swarm optimization (Expand Search), codon optimization (Expand Search)
based objective » based object (Expand Search), based selective (Expand Search), based objects (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
gene used » genes used (Expand Search), gene based (Expand Search), were used (Expand Search)
used from » use from (Expand Search)
from optimization » fox optimization (Expand Search), swarm optimization (Expand Search), codon optimization (Expand Search)
based objective » based object (Expand Search), based selective (Expand Search), based objects (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
gene used » genes used (Expand Search), gene based (Expand Search), were used (Expand Search)
used from » use from (Expand Search)
-
1
-
2
-
3
-
4
-
5
-
6
Proposed Algorithm.
Published 2025“…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …”
-
7
Comparisons between ADAM and NADAM optimizers.
Published 2025“…The objective is to optimize binary offloading decisions under dynamic wireless channel conditions and energy harvesting constraints. …”
-
8
-
9
-
10
-
11
-
12
Model performance using several supervised machine-learning algorithms.
Published 2021“…<p>Various machine-learning algorithms were evaluated using the entire feature set (n = 3065 genes) and the <i>Clairvoyance</i>-optimized feature set (<i>GeneSet</i><sub><i>y1-y5</i></sub>, n = 399 genes) with the same LCOCV pairs. …”
-
13
-
14
-
15
-
16
Datasets used in the experiment [3].
Published 2025“…This paper summarizes the models available in the literature, briefly introduces transformers, then offers a novel deep learning model and evaluates various design alternatives, including k-mer size, number of core modules, choice of optimization algorithm, and whether to use self-attention. …”
-
17
-
18
<i>In silico</i> prediction of blood cholesterol levels from genotype data
Published 2020“…<div><p>In this work we present a framework for blood cholesterol levels prediction from genotype data. The predictor is based on an algorithm for cholesterol metabolism simulation available in literature, implemented and optimized by our group in the R language. …”
-
19
-
20