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4 papers · 2 filters
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…
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…
WinFLoRA: Incentivizing Client-Adaptive Aggregation in Federated LoRA under Privacy Heterogeneity
Mengsha Kou, Xiaoyu Xia, Ziqi Wang +4
Large Language Models (LLMs) increasingly underpin intelligent web applications, from chatbots to search and recommendation, where efficient specialization is essential. Low-Rank A…
Approximation Algorithm for Constrained -Center Clustering: A Local Search Approach
Chaoqi Jia, Longkun Guo, Kewen Liao +3
Clustering is a long-standing research problem and a fundamental tool in AI and data analysis. The traditional k-center problem, a fundamental theoretical challenge in clustering,…