In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
Most current work in data mining assumes that the database is static, and a database update requires rediscovering all the patterns by scanning the entire old and new database. Su...
Time series data is usually stored and processed in the form of discrete trajectories of multidimensional measurement points. In order to compare the measurements of a query traje...
Similarity-based search over time-series databases has been a hot research topic for a long history, which is widely used in many applications, including multimedia retrieval, dat...
Qiuxia Chen, Lei Chen 0002, Xiang Lian, Yunhao Liu...
We develop new techniques for time series classification based on hierarchical Bayesian generative models (called mixed-effect models) and the Fisher kernel derived from them. A k...