4 citations · 7 across the 4 of their papers we have counts for
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stat.ML2022
Decentralized Hyper-Gradient Computation over Time-Varying Directed Networks
Naoyuki Terashita, Satoshi Hara
This paper addresses the communication issues when estimating hyper-gradients in decentralized federated learning (FL). Hyper-gradients in decentralized FL quantifies how the perfo…
stat.ML2021★ 4 cited
Influence Estimation for Generative Adversarial Networks
Naoyuki Terashita, Hiroki Ohashi, Yuichi Nonaka +1
Identifying harmful instances, whose absence in a training dataset improves model performance, is important for building better machine learning models. Although previous studies h…