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Your search keyword '"Wei, Jiakai"' showing total 11 results
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11 results on '"Wei, Jiakai"'

1. The Design and Analysis of 3D Braiding Mechanism Based on a Small-Size Additive Manufacturing Technology Reinforced by Continuous Fiber

Author

Wei, Jiakai, Han, Wenpeng, Zhang, Wuxiang, Ding, Xilun, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Haddar, Mohamed, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, and Liu, Xinjun, editor

Published
2023
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3. Forget the Learning Rate, Decay Loss

Author

Wei, Jiakai

Subjects
Computer Science - Machine Learning
Abstract

In the usual deep neural network optimization process, the learning rate is the most important hyper parameter, which greatly affects the final convergence effect. The purpose of learning rate is to control the stepsize and gradually reduce the impact of noise on the network. In this paper, we will use a fixed learning rate with method of decaying loss to control the magnitude of the update. We used Image classification, Semantic segmentation, and GANs to verify this method. Experiments show that the loss decay strategy can greatly improve the performance of the model, Comment: Asia Conference on Machine Learning and Computing. arXiv admin note: text overlap with arXiv:1703.04782, arXiv:1611.07004 by other authors

Published
2019

4. Fast, Better Training Trick -- Random Gradient

Author

Wei, Jiakai

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

In this paper, we will show an unprecedented method to accelerate training and improve performance, which called random gradient (RG). This method can be easier to the training of any model without extra calculation cost, we use Image classification, Semantic segmentation, and GANs to confirm this method can improve speed which is training model in computer vision. The central idea is using the loss multiplied by a random number to random reduce the back-propagation gradient. We can use this method to produce a better result in Pascal VOC, Cifar, Cityscapes datasets., Comment: arXiv admin note: text overlap with arXiv:1708.07120 by other authors

Published
2018

11. [Isovaleric acidemia due to compound heterozygous variants of IVD gene in a case].

Author

Che F, Yang Y, Wang Z, Wang G, Wu H, Zhang L, Wei J, Zhao Y, and Zhao J

Subjects
Child, Female, Heterozygote, Humans, Isovaleryl-CoA Dehydrogenase genetics, Male, Mutation, Amino Acid Metabolism, Inborn Errors genetics, Isovaleryl-CoA Dehydrogenase deficiency
Abstract

Objective: To analyze the clinical features, biochemical characteristics and molecular pathogenesis of a girl with isovaleric acidemia., Methods: Clinical features, blood spot amino acid profiles and urinary organic acid profiles of the patient were analyzed. Targeted capture, next generation sequencing and Sanger sequencing were carried out to detect potential variant of the IVD gene., Results: The patient presented with poor weight gain, poor feeding, lethargy, and a "sweaty feet" odor 10 days after birth. Biochemical test suggested hyperammonemia. Blood spot amino acid profiles displayed a dramatic increase in isovalerylcarnitine (C5: 3. 044, reference range 0.04 - 0.4 μmol/L). Organic acid analysis of her urine sample revealed a high level of isovaleric glycine (669. 53, reference range 0 - 0.5). The child was ultimately diagnosed with isovaleric acidemia, and was found to harbor a paternally derived heterozygous variant c.149G>A (p.R50H) and a maternally derived heterozygous variant c.1123G>A (p.G375S) of the IVD gene. Her elder brother was a heterozygous carrier of c.1123G>A (p.G375S) variant. The c.149G>A (p.R50H) was a known pathogenic variant, while the c.1123G>A (p.G375S) variant was previously unreported., Conclusion: The pathogenesis of the patient was delineated from the perspective of genetics, which has provided a basis for clinical diagnosis, treatment as well as genetic counseling.

Published
2021
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