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Longitudinal quantitative assessment of macular retinal and choroidal remodeling after trabeculectomy in chronic primary angle-closure glaucoma using ultra-widefield SS-OCTA. [PDF]
Sci RepGuo Y, Zhao J, Chen Z.
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Carotid Arteries in Cerebral Small Vessel Disease and Dementia
Kitajima E +12 more
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ACM Transactions on Internet Technology, 2020
Recommendation systems have been widely used in large e-commerce websites, but cold start and data sparsity seriously affect the accuracy of recommendation. To solve these problems, we propose SSL-SVD, which works to mine the sparse trust between users and improve the performance of the recommendation system.
Zhengdi Hu +7 more
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Recommendation systems have been widely used in large e-commerce websites, but cold start and data sparsity seriously affect the accuracy of recommendation. To solve these problems, we propose SSL-SVD, which works to mine the sparse trust between users and improve the performance of the recommendation system.
Zhengdi Hu +7 more
openaire +1 more source
Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 2014
Singular Value Decomposition (SVD) is computationally costly and therefore a naive implementation does not scale to the needs of scenarios where data evolves continuously. While there are various on-line analysis and incremental decomposition techniques, these may not accurately represent the data or may be slow for the needs of many applications.
Xilun Chen, K. Selcuk Candan
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Singular Value Decomposition (SVD) is computationally costly and therefore a naive implementation does not scale to the needs of scenarios where data evolves continuously. While there are various on-line analysis and incremental decomposition techniques, these may not accurately represent the data or may be slow for the needs of many applications.
Xilun Chen, K. Selcuk Candan
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K-SVD Meets Transform Learning: Transform K-SVD
IEEE Signal Processing Letters, 2014Recently there has been increasing attention directed towards the analysis sparsity models. Consequently, there is a quest for learning the operators which would enable analysis sparse representations for signals in hand. Analysis operator learning algorithms such as the Analysis K-SVD have been proposed.
Ender M. Eksioglu, Ozden Bayir
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IEEE Signal Processing Letters, 2017
The problem of dictionary learning (DL) for sparse representations can be approximately solved by several algorithms. Regularization of the optimization objective (representation error) was proved useful, since it avoids possible bottlenecks due to nearly linearly dependent atoms.
Bogdan Dumitrescu, Paul Irofti
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The problem of dictionary learning (DL) for sparse representations can be approximately solved by several algorithms. Regularization of the optimization objective (representation error) was proved useful, since it avoids possible bottlenecks due to nearly linearly dependent atoms.
Bogdan Dumitrescu, Paul Irofti
openaire +1 more source