This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...
We present a model that improves entity entity link modeling in a mixed membership stochastic block model, by jointly modeling links with text about the entities that are linked i...
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
There has been much recent work on algorithms for limiting disclosure in data publishing. However, these algorithms have not been put to use in any comprehensive, usable toolkit f...
In this multi-university collaborative research, we will develop a framework for the dynamic data-driven fault diagnosis of wind turbines which aims at making the wind energy a com...
Yu Ding, Eunshin Byon, Chiwoo Park, Jiong Tang, Yi...