8 citations · 12 across the 8 of their papers we have counts for
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cs.LG2023★ 8 cited
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes
Zhen Qin, Daoyuan Chen, Bingchen Qian +3
Pre-trained large language models (LLMs) need fine-tuning to improve their responsiveness to natural language instructions. Federated learning offers a way to fine-tune LLMs using…
cs.LG2023
Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Time Series Anomaly Detection
Feiyi Chen, Yingying zhang, Zhen Qin +5
Anomaly detection significantly enhances the robustness of cloud systems. While neural network-based methods have recently demonstrated strong advantages, they encounter practical…
cs.LG2023★ 1 cited
LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection
Feiyi Chen, Zhen Qin, Yingying Zhang +4
Most of current anomaly detection models assume that the normal pattern remains same all the time. However, the normal patterns of Web services change dramatically and frequently.…