2 research outputs found
Mutual Information Decay Curves and Hyper-Parameter Grid Search Design for Recurrent Neural Architectures
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.Comment: Published at the 27th International Conference on Neural Information
Processing, ICONIP 2020, Bangkok, Thailand, November 18-22, 2020. arXiv admin
note: text overlap with arXiv:1810.0296