2k citations · 5.9k across the 38 of their papers we have counts for
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cs.NE2018★ 25 cited
Guided evolutionary strategies: Augmenting random search with surrogate gradients
Niru Maheswaranathan, Luke Metz, George Tucker +2
Many applications in machine learning require optimizing a function whose true gradient is unknown, but where surrogate gradient information (directions that may be correlated with…
cs.NE2017★ 376 cited
Regularizing Neural Networks by Penalizing Confident Output Distributions
Gabriel Pereyra, George Tucker, Jan Chorowski +2
We systematically explore regularizing neural networks by penalizing low entropy output distributions. We show that penalizing low entropy output distributions, which has been show…