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Zeroth-Order Topological Insights into Iterative Magnitude Pruning
Modern-day neural networks are famously large, yet also highly redundant and compressible; there exist numerous pruning strategies in the deep learning literature that yield over 90% sparser sub-networks of fully-trained, dense architectures while still maintaining their original accuracies.
High-Capacity Complex Convolutional Neural Networks For I/Q Modulation Classification
I/Q modulation classification is a unique pattern recognition problem as the data for each class varies in quality, quantified by signal to noise ratio (SNR), and has structure in the complex-plane.
Modulation Pattern Detection Using Complex Convolutions in Deep Learning
Transceivers used for telecommunications transmit and receive specific modulation patterns that are represented as sequences of complex numbers.
