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cs.LG2026
A Multi-Step Inertial ADMM Algorithm for Federated Learning
Hao Li, Qingsong Wang, Xihong Yan +2
Federated learning has recently emerged as an important paradigm for large-scale distributed model training, which can be naturally formulated as a class of distributed learning pr…
cs.LG2026
Decoupled Structure-Feature Alignment via Alternating Optimization for Graph Learning
Chengcheng Yan, Feifei Zhao, Dai Zhu +2
Conventional Graph Neural Networks (GNNs) couple feature transformation and neighborhood aggregation, which often renders them vulnerable to topological noise and heterophilous con…