NSF-CSSI-2020-Talk-Zhenming-LIU.pdf (2.2 MB)

A high performance suite of SVD related solvers for machine learning

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posted on 31.01.2020 by Zhenming Liu, Andreas Stathopoulos
We present our recent research progress on joint-optimization for ML algorithm and SVD solver. Our major discovery is that the "stopping criteria" of a SVD algorithm can be directly optimized for downstream ML applications. We will present a few examples, in which when we change the stopping criteria of the "inner SVD algorithm", we see significant performance gain (in running time) in the "outer" ML algorithm.

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Elements: Software: NSCI: A high performance suite of SVD related solvers for machine learning

Directorate for Computer & Information Science & Engineering

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