BinomMAML uses a binomial expansion to estimate meta-gradients more accurately than prior approximations, with error bounds that improve on existing methods and decay super-exponentially under mild conditions.
, K , P0 t :=I d, and dummy index k0 =−1
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Binomial Gradient-Based Meta-Learning for Enhanced Meta-Gradient Estimation
BinomMAML uses a binomial expansion to estimate meta-gradients more accurately than prior approximations, with error bounds that improve on existing methods and decay super-exponentially under mild conditions.