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Found 3 papers, 2 papers with code
Topological Insights into Sparse Neural Networks
However, comparing different sparse topologies and determining how sparse topologies evolve during training, especially for the situation in which the sparse structure optimization is involved, remain as challenging open questions.
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders
This method, named QuickSelection, introduces the strength of the neuron in sparse neural networks as a criterion to measure the feature importance.
Online Distributed Evolutionary Optimization of Time Division Multiple Access Protocols
With the advent of cheap, miniaturized electronics, ubiquitous networking has reached an unprecedented level of complexity, scale and heterogeneity, becoming the core of several modern applications such as smart industry, smart buildings and smart cities.
