Zobrazeno 1 - 10
of 295
pro vyhledávání: '"Gradient learning"'
Autor:
Chunyang Zhang, Wenjing Han
Publikováno v:
PeerJ Computer Science, Vol 10, p e2387 (2024)
Employee turnover has a negative impact on business profitability. To tackle this issue, we can utilize computational advancements to forecast attrition and minimize expenses. We employed an HR Analytics dataset to investigate the feasibility of usin
Externí odkaz:
https://doaj.org/article/2ecff63e16b643bb9783bca4e7122eaa
Akademický článek
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Publikováno v:
Remote Sensing, Vol 15, Iss 21, p 5174 (2023)
Hyperspectral imaging often suffers from various types of noise, including sensor non-uniformity and atmospheric disturbances. Removing multiple types of complex noise in hyperspectral images (HSIs) while preserving high fidelity in spectral dimensio
Externí odkaz:
https://doaj.org/article/1dfcc7ef6d43465e997e40df4b92e195
Autor:
Alexandre Bittar, Philip N. Garner
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Artificial neural networks (ANNs) are the basis of recent advances in artificial intelligence (AI); they typically use real valued neuron responses. By contrast, biological neurons are known to operate using spike trains. In principle, spiking neural
Externí odkaz:
https://doaj.org/article/c1a6dcd9a7a44a098615d39baaac6419
Publikováno v:
EURASIP Journal on Wireless Communications and Networking, Vol 2021, Iss 1, Pp 1-9 (2021)
Abstract In this paper, the blind signal separation problem of complex baseband signal is addressed. A widely linear complex autoregressive process of order one is employed to represent the temporal structure of complex sources. We formulate a new co
Externí odkaz:
https://doaj.org/article/1a3f70cfe00e47808d005555105152fa
Publikováno v:
IEEE Access, Vol 9, Pp 158548-158561 (2021)
Parallelization of tasks and efficient utilization of processors are considered important and challenging in operating large-scale real-time systems. Recently, deep reinforcement learning (DRL) was found to provide effective solutions to various comb
Externí odkaz:
https://doaj.org/article/e58938209a6d4545810e3bb890964cca
Autor:
Khidir Shaib Mohamed
Publikováno v:
Computers, Vol 12, Iss 1, p 4 (2022)
Regularization techniques are critical in the development of machine learning models. Complex models, such as neural networks, are particularly prone to overfitting and to performing poorly on the training data. L1 regularization is the most extreme
Externí odkaz:
https://doaj.org/article/a653afa5d78b402097e464de3f641831
Publikováno v:
Entropy, Vol 24, Iss 7, p 956 (2022)
Gradient Learning (GL), aiming to estimate the gradient of target function, has attracted much attention in variable selection problems due to its mild structure requirements and wide applicability. Despite rapid progress, the majority of the existin
Externí odkaz:
https://doaj.org/article/cc41992bb9794a6aaadbe41d2c9b176d
Publikováno v:
Frontiers in Neuroscience, Vol 14 (2020)
The two possible pathways toward artificial intelligence (AI)—(i) neuroscience-oriented neuromorphic computing [like spiking neural network (SNN)] and (ii) computer science driven machine learning (like deep learning) differ widely in their fundame
Externí odkaz:
https://doaj.org/article/ce20a73ff08b41b6ac016b2414bcf56d
Akademický článek
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