Gauss quadrature for matrix inverse forms with applications
We present a framework for accelerating a spectrum of machine learning algorithms that require computation of bilinear inverse forms u[superscript T] A[superscript −1]u, where A is a positive definite matrix and u a given vector. Our framework is built on Gauss-type quadrature and easily scales to...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Proceedings of Machine Learning Research
2017
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| Online Access: | http://hdl.handle.net/1721.1/113000 https://orcid.org/0000-0003-1532-3083 https://orcid.org/0000-0001-8516-4925 https://orcid.org/0000-0002-6121-9474 |