MEMe: An accurate maximum entropy method for efficient approximations in large-scale machine learning
Efficient approximation lies at the heart of large-scale machine learning problems. In this paper, we propose a novel, robust maximum entropy algorithm, which is capable of dealing with hundreds of moments and allows for computationally efficient approximations. We showcase the usefulness of the pro...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Published: |
MDPI
2019
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