DepTGL, a scalable distributed training framework that restructures temporal-dependency management for M-TGNNs from a data-centric perspective, introduces a hybrid temporal-dependency management scheme that explicitly balances communication and caching overhead via temporal-event caching, supplemented by selective depe...
Lin-Fang Chen, Zhen Song, Lei Liu et al.· 0 citations
Modern OLTP applications, such as financial fraud detection and stock risk management, rely on analytical queries for real-time decision-making. In these scenarios, queries must access the freshest data without disrupting the performance of mission-critical transactions. We characterize them as
transaction-centric...
Ze-Shun Peng, Qin-Cheng Cai, Si-Yuan Wei et al.· Proceedings of the ACM on Ma...· 0 citations
ReCATS combines multi-regime modeling with a dual-phase generative alignment mechanism, enabling effective adaptation to distribution shifts while preserving knowledge acquired from past tasks, and introduces a dynamic dual-scale thresholding strategy to mitigate decision boundary drift under evolving data distribution...
Qiuyang Li, Qian Ma, Zhong-Ming Yao et al.· Proceedings of the 32nd ACM...· 0 citations
Multivariate time series anomaly detection is critical in safety-critical domains such as industrial monitoring and financial systems. However, real-world time series are inherently non-stationary, with evolving data distributions driven by changing operational regimes and system dynamics. As a result, most existing me...
Qiuyang Li, Q. Ma, Zhongming Yao et al.· Proceedings of the 32nd ACM...· 0 citations
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