4 papers
Agent System Operations: Categorization, Challenges, and Future Directions
Zexin Wang, Changhua Pei, Yuanhao Liu +10
As the reasoning capabilities of Large Language Models (LLMs) continue to advance, LLM-based agent systems offer advantages in flexibility and interpretability over traditional sys…
Strong Linear Baselines Strike Back: Closed-Form Linear Models as Gaussian Process Conditional Density Estimators for TSAD
Aleksandr Yugay, Hang Cui, Changhua Pei +1
Research in time series anomaly detection (TSAD) has largely focused on developing increasingly sophisticated, hard-to-train, and expensive-to-infer neural architectures. We revisi…
ViTs: Teaching Machines to See Time Series Anomalies Like Human Experts
Zexin Wang, Changhua Pei, Yang Liu +8
Web service administrators must ensure the stability of multiple systems by promptly detecting anomalies in Key Performance Indicators (KPIs). Achieving the goal of "train once, in…
TShape: Rescuing Machine Learning Models from Complex Shapelet Anomalies
Hang Cui, Jingjing Li, Haotian Si +4
Time series anomaly detection (TSAD) is critical for maintaining the reliability of modern IT infrastructures, where complex anomalies frequently arise in highly dynamic environmen…