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pro vyhledávání: '"Jiang, Arthur"'
Autor:
Ma, Xin, Bao, Renyi, Jiang, Jinpeng, Liu, Yang, Jiang, Arthur, Yan, Jun, Liu, Xin, Pan, Zhisong
In this work, we propose FedSSO, a server-side second-order optimization method for federated learning (FL). In contrast to previous works in this direction, we employ a server-side approximation for the Quasi-Newton method without requiring any trai
Externí odkaz:
http://arxiv.org/abs/2206.09576
Multi-agent reinforcement learning (MARL) has been increasingly explored to learn the cooperative policy towards maximizing a certain global reward. Many existing studies take advantage of graph neural networks (GNN) in MARL to propagate critical col
Externí odkaz:
http://arxiv.org/abs/2012.13099
Autor:
Li, Guoliang *, Wei, Hui *, Jiang, Arthur *, Hu, Jian *, Yan, Jun *, Li, Linfeng *, Wang, Jianxiang
Publikováno v:
In Blood 15 November 2022 140 Supplement 1:7834-7835