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Versatile sparse matrix factorization: Theory and applications
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由 Y Li 著作2014被引用 14 次 — In this paper, we propose a unified matrix factorization model, coined versatile sparse matrix factorization (VSMF) model, for biological data analysis.
Versatile sparse matrix factorization: Theory and applications
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由 Y Li 著作2014被引用 14 次 — We discuss the modelling, optimization, and applications of VSMF. We show that many well-known sparse matrix factorization models are specific cases of our VSMF ...
Versatile sparse matrix factorization: Theory and applications
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Determining the number of clusters in high-dimensional real-life datasets and interpreting the final outcome are among the challenging problems in data science.
Versatile sparse matrix factorization: Theory and applications
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The proposed non-negative matrix factorization with multiple constraints model is shown to be capable of efficiently recovering diagonal block structures ...
Versatile Sparse Matrix Factorization and Its Applications in ...
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由 Y Li 著作2013被引用 20 次 — Non-negative matrix factorization and sparse representation models have been successfully applied in high-throughput biological data analysis.
Versatile sparse matrix factorization: Theory and applications.
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Bibliographic details on Versatile sparse matrix factorization: Theory and applications.
Versatile Sparse Matrix Factorization and Its Applications in High ...
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Versatile sparse matrix factorization: Theory and applications · Coordinate Descent-Based Sparse Nonnegative Matrix Factorization for Robust Cancer-Class ...
Versatile Sparse Matrix Factorization and Its Applications in High ...
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This paper proposes the versatile sparse matrix factorization (VSMF) model for biological data mining and shows that many well-known sparse models are ...
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Sparse representations with applications in imaging ...
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2024年10月22日 — In this paper, we propose an unified matrix factorization model, coined versatile sparse matrix factorization (VSMF) model, for biological data ...
Trapezoid: A Versatile Accelerator for Dense and Sparse ...
Massachusetts Institute of Technology
https://people.csail.mit.edu › emer › media › papers
Massachusetts Institute of Technology
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由 Y Yang 著作 — While most deployed accelerators target multiplication of dense matrices, many applications compute on sparse data, i.e., those with a large fraction of zeros.
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