[1903.01611] The Lottery Ticket Hypothesis at Scale


MIT PhD student and Google Brain researcher Jonathan Frankle follows up his early work on neural network pruning and optimizing by testing the “Lottery Ticket Hypothesis at Scale”. Previously, Frankle et al showed that for relatively small neural networks performing simple tasks, the vast majority (over 99%) of trained network weights could be removed without significantly impacting accuracy. This paper tests the same idea on larger, more complex networks like ResNet50 with similar results.


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