Symbolic Regression for Data Storage with Side Information
X Zuo, AA Jiang, N Raviv… - 2022 IEEE Information …, 2022 - ieeexplore.ieee.org
2022 IEEE Information Theory Workshop (ITW), 2022•ieeexplore.ieee.org
There are various ways to use machine learning to improve data storage techniques. In this
paper, we introduce symbolic regression, a machine-learning method for recovering the
symbolic form of a function from its samples. We present a new symbolic regression scheme
that utilizes side information for higher accuracy and speed in function recovery. The
scheme enhances latest results on symbolic regression that were based on recurrent neural
networks and genetic programming. The scheme is tested on a new benchmark of functions …
paper, we introduce symbolic regression, a machine-learning method for recovering the
symbolic form of a function from its samples. We present a new symbolic regression scheme
that utilizes side information for higher accuracy and speed in function recovery. The
scheme enhances latest results on symbolic regression that were based on recurrent neural
networks and genetic programming. The scheme is tested on a new benchmark of functions …
There are various ways to use machine learning to improve data storage techniques. In this paper, we introduce symbolic regression, a machine-learning method for recovering the symbolic form of a function from its samples. We present a new symbolic regression scheme that utilizes side information for higher accuracy and speed in function recovery. The scheme enhances latest results on symbolic regression that were based on recurrent neural networks and genetic programming. The scheme is tested on a new benchmark of functions for data storage.
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