Anomaly Detection and Sequential Filtering with Partial Observations
Friday, July 19, 2019|
3:00pm - 5:00pm
Add to Google Calendar
About the Event
Abstract: With the rise of "big data" where any and all data is collected, comes a series of new challenges involving the computation and analysis of such massive data sets. Nowadays, data is continuously collected leading to questions of at which point should analysis begin and how to incorporate new data into the analysis. Additionally, within the massive amounts of data collected, the features of interest may not be directly observed or only a small subset of the data with certain properties may be of interest. And while collecting data is "cheap", labeling data often is not. In this talk, I will touch upon models for data with partial labels, latent variables, and anomalies in scenarios where such data is continuously being collected. I will also outline some real world applications including cyber security, transportation, and weather systems.
Sponsor(s): Professor Alfred Hero
Open to: Public