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WhenDoFlatMinimaOptimizers Work?
Neural Information Processing Systems
Theoretical and empirical studies [21,77,9,55,49,5,12]postulate that such flatter regions generalize better than sharper minima, e.g., due to the flat minimizer's robustness against loss function shifts between trainandtestdata,asillustrated inFig.1.
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RankAssumptions
Neural Information Processing Systems
Kernel methods augmented with random features give scalable algorithms for learning from big data.
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