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cs.LG2024
A Granger-Causal Perspective on Gradient Descent with Application to Pruning
Aditya Shah, Aditya Challa, Sravan Danda +2
Stochastic Gradient Descent (SGD) is the main approach to optimizing neural networks. Several generalization properties of deep networks, such as convergence to a flatter minima, a…
cs.LG2023
To prune or not to prune : A chaos-causality approach to principled pruning of dense neural networks
Rajan Sahu, Shivam Chadha, Nithin Nagaraj +2
Reducing the size of a neural network (pruning) by removing weights without impacting its performance is an important problem for resource-constrained devices. In the past, pruning…