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On Training Implicit Meta-Learning With Applications to Inductive Weighing in Consistency Regularization
In this study, we start by conducting a systematic comparative analysis of the various approximation methods and their effect when incorporated into IML training routines.
Is Scaling Learned Optimizers Worth It? Evaluating The Value of VeLO's 4000 TPU Months
We analyze VeLO (versatile learned optimizer), the largest scale attempt to train a general purpose "foundational" optimizer to date.
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