100 citations
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Showing cs.LGShow all
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cs.LG2026
On the Push-Based Asynchronous Federated Learning: A Bias-Correction Aggregation Approach
Jiahui Bai, Hai Dong, A. K. Qin
Asynchronous decentralized federated learning (ADFL) eliminates central coordination and global synchronization, making it attractive for large-scale and heterogeneous systems. How…
cs.LG2026
EventADL: Open-Box Anomaly Detection and Localization Framework for Events in Cloud-Based Service Systems
Luan Pham, Victor Nicolet, Joey Dodds +2
Anomaly detection and localization (ADL) is critical for maintaining reliability and availability in cloud systems. Recent ADL developments focus on metric and log data, leaving ev…
cs.LG2026★ 100 cited
Graph Neural Networks for Graphs with Heterophily: A Survey
Xin Zheng, Yi Wang, Yixin Liu +5
Recent years have witnessed fast developments of graph neural networks (GNNs) that have benefited myriad graph analytic tasks and applications. Most GNNs rely on the homophily assu…