141 citations · 285 across the 14 of their papers we have counts for
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cs.LG2019★ 5 cited
Learning Effective Loss Functions Efficiently
Matthew Streeter
We consider the problem of learning a loss function which, when minimized over a training dataset, yields a model that approximately minimizes a validation error metric. Though lea…
cs.LG2019★ 1 cited
Bayes Optimal Early Stopping Policies for Black-Box Optimization
Matthew Streeter
We derive an optimal policy for adaptively restarting a randomized algorithm, based on observed features of the run-so-far, so as to minimize the expected time required for the alg…
cs.LG2019★ 1 cited
Learning Optimal Linear Regularizers
Matthew Streeter
We present algorithms for efficiently learning regularizers that improve generalization. Our approach is based on the insight that regularizers can be viewed as upper bounds on the…