Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A better understanding of pruning methods based on a ranking of ights according to their saliency in a trained network requires further information on the statistical properties of such saliencies.  focus on two-layer networks with either a linear or nonlinear output unit, and obtain analytic expressions for the distribution of saliencies and their logarithms. Our results reveal unexpected universal properties of the log-saliency distribution and suggest a novel algorithm for saliency-based ight ranking that avoids the numerical cost of second derivative evaluations.
['Jan Gorodkin', 'Lars Kai Hansen', 'B. Lautrup', 'Sara A. Solla']
I am writing a research paper on a idea Universal distribution of saliencies for pruning in layered neural networks.
[{"from": "human", "value": "I am writing a research paper on a idea Universal distribution of saliencies for pruning in layered neural networks."}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A better understanding of pruning methods based on a ranking of ights according to their saliency in a trained network requires further information on the statistical properties of such saliencies.  focus on two-layer networks with either a linear or nonlinear output unit, and obtain analytic expressions for the distribution of saliencies and their logarithms. Our results reveal unexpected universal properties of the log-saliency distribution and suggest a novel algorithm for saliency-based ight ranking that avoids the numerical cost of second derivative evaluations."}]