7 citations · 7 across the 3 of their papers we have counts for
5 papers
Federated Variational Learning for Anomaly Detection in Multivariate Time Series
Kai Zhang, Yushan Jiang, Lee Seversky +3
Anomaly detection has been a challenging task given high-dimensional multivariate time series data generated by networked sensors and actuators in Cyber-Physical Systems (CPS). Bes…
Factor Analysis on Citation, Using a Combined Latent and Logistic Regression Model
Namjoon Suh, Xiaoming Huo, Eric Heim +1
We propose a combined model, which integrates the latent factor model and the logistic regression model, for the citation network. It is noticed that neither a latent factor model…
Sequential Low-Rank Change Detection
Yao Xie, Lee Seversky
Detecting emergence of a low-rank signal from high-dimensional data is an important problem arising from many applications such as camera surveillance and swarm monitoring using se…
Active Perceptual Similarity Modeling with Auxiliary Information
Eric Heim, Matthew Berger, Lee Seversky +1
Learning a model of perceptual similarity from a collection of objects is a fundamental task in machine learning underlying numerous applications. A common way to learn such a mode…
Efficient Online Relative Comparison Kernel Learning
Eric Heim, Matthew Berger, Lee M. Seversky +1
Learning a kernel matrix from relative comparison human feedback is an important problem with applications in collaborative filtering, object retrieval, and search. For learning a…