Results 121 to 130 of about 482,653 (299)
, 2018 Transfer learning is a machine learning technique designed to improve generalization performance by using pre-trained parameters obtained from other learning tasks.
Kido, Shoji +3 more
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Causal Feature Selection via Transfer Entropy
2024 International Joint Conference on Neural Networks (IJCNN)Machine learning algorithms are designed to capture complex relationships between features. In this context, the high dimensionality of data often results in poor model performance, with the risk of overfitting. Feature selection, the process of selecting a subset of relevant and non-redundant features, is, therefore, an essential step to mitigate ...
Paolo Bonetti +2 more
openaire +3 more sources
FEBS Letters, EarlyView.The pyruvate generator, which causes activation of respiration by extra‐mitochondrial Ca2+, is also present and functional in rat brainstem mitochondria, as it is in other brain regions. This finding is confirmed by experiments with a fully reconstituted malate–aspartate shuttle (MAS).
Grazyna Debska‐Vielhaber +7 more
wiley +1 more source
The ubiquitin‐proteasome system and autophagy as guardians of the cellular proteome
FEBS Letters, EarlyView.This Perspective covers the three principles governing the crosstalk between the ubiquitin‐proteasome system and autophagy in cellular proteostasis: (1) a shared ubiquitin code routing substrates via shuttle factors or autophagy receptors; (2) spatial compartmentalization into phase‐separated degradation hubs and organelle‐specific modules (exemplified
Ivan Dikic
wiley +1 more source
Multi-modal cascade feature transfer for polymer property prediction
Machine Learning: Science and TechnologyIn this paper, we propose a novel transfer learning approach called multi-modal cascade model with feature transfer for polymer property prediction.
Kiichi Obuchi +4 more
doaj +1 more source
Correlation‐guided multi‐object tracking with correlation feature transfer
IET Computer Vision, 2019 Here, the authors propose a correlation‐guided Monte Carlo Markov chain (MCMC) solver to promote the efficiency for tracking multiple objects under recursive Bayesian filtering framework.
Jiatong Li, Yanjie Zhao, Zhiguo Jiang
doaj +1 more source
FEBS Letters, EarlyView.An unexpected alternative interaction site for ethyl viologen was identified in formate dehydrogenase 1 from Methylorubrum extorquens. Combined mutagenesis, kinetic analysis, and docking revealed that aromatic residues near an iron–sulfur cluster enable flavin mononucleotide‐independent electron transfer, offering a framework for engineering improved ...
Eleni G. Poloniataki, Yong Hwan Kim
wiley +1 more source
Understanding Slow Feature Analysis: A Mathematical Framework
, 2008 Slow feature analysis is an algorithm for unsupervised learning of invariant representations from data with temporal correlations. Here, we present a mathematical analysis of slow feature analysis for the case where the input-output functions are not ...
Wiskott, Dr. Laurenz +1 more
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Ubiquitination of secretory granules promotes their crinophagic degradation in Drosophila
FEBS Letters, EarlyView.Ubiquitination of secretory granules in Drosophila larval salivary glands is a critical molecular trigger for crinophagy, the lysosomal degradation of unreleased, or low‐quality granules. The E3 ubiquitin ligase Cnot4 is recruited to the surface of secretory granules to induce crinophagy.
Tamás Csizmadia +6 more
wiley +1 more source
Good Practice in CNN Feature Transfer [PDF]
The objective of this paper is the effective transfer of the Convolutional Neural Network (CNN) feature in image search and classification. Systematically, we study three facts in CNN transfer.
Zheng, L +4 more
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