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arXiv · 2012.04632

Mutual Information Decay Curves and Hyper-Parameter Grid Search Design for Recurrent Neural Architectures

Abhijit Mahalunkar·John D. Kelleher
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Abstract

We present an approach to design the grid searches for hyper-parameter optimization for recurrent neural architectures. The basis for this approach is the use of mutual information to analyze long distance dependencies (LDDs) within a dataset. We also report a set of experiments that demonstrate how using this approach, we obtain state-of-the-art results for DilatedRNNs across a range of benchmark datasets.

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Abhijit Mahalunkar, John D. Kelleher. 2020-12-08. Mutual Information Decay Curves and Hyper-Parameter Grid Search Design for Recurrent Neural Architectures. https://doi.org/10.1007/978-3-030-63823-8_70

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