In the era of big data and Artificial Intelligence, an emerging paradigm is to utilize contrastive
self-supervised learning to model large-scale heterogeneous data. Many existing foundation …

In the era of observability, massive amounts of time series data have been collected to
monitor the running status of the target system, where anomaly detection serves to identify …

With the expanding scale of current industries, monitoring systems centered around Key
Performance Indicators (KPIs) play an increasingly crucial role. KPI anomaly detection can …

Data augmentation plays a critical role in self-supervised learning, including anomaly
detection. While hand-crafted transformations such as image rotations can achieve …

As a critical technology, anomaly detection ensures the smooth operation of cloud systems
while maintaining the market competitiveness of cloud service providers. However, the …

Identifying anomalies from time series data plays an important role in various fields such as
infrastructure security, intelligent operation and maintenance, and space exploration …

Anomaly detection (AD) plays a critical role in a wide variety of big data applications,
including cybersecurity, monitoring, and network systems. It consists in finding patterns in …