167 citations · 257 across the 7 of their papers we have counts for
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cs.NE2018
Understanding and correcting pathologies in the training of learned optimizers
Luke Metz, Niru Maheswaranathan, Jeremy Nixon +2
Deep learning has shown that learned functions can dramatically outperform hand-designed functions on perceptual tasks. Analogously, this suggests that learned optimizers may simil…
cs.NE2018
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…