C NUMERICAL TEST SETUPS All experiments are implemented on a desktop with an NVIDIA RTX A5000 GPU, and a server with NVIDIA A100 GPUs

= K−1 L γL+1 + (γ+ 1)S[K−1] (d) = K−L+1X l=1 K−l L γL+1(1 +γ) l−1 + (1 +γ) K−L−1 S[L+ 1] =γ L+1 K−LX l=1 K−l L (1 +γ) l−1 where (a) is due to K l = K−1 l−1 + K−1 l for L+ 1≤l≤K−1, K K = 1 = K−1 K−1 , (b) changes the index in the first su · 2026

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Binomial Gradient-Based Meta-Learning for Enhanced Meta-Gradient Estimation

cs.LG · 2026-04-14 · unverdicted · novelty 6.0

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.

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Binomial Gradient-Based Meta-Learning for Enhanced Meta-Gradient Estimation cs.LG · 2026-04-14 · unverdicted · none · ref 15
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.

C NUMERICAL TEST SETUPS All experiments are implemented on a desktop with an NVIDIA RTX A5000 GPU, and a server with NVIDIA A100 GPUs

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