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 ...
Abstract—Community detection or cluster detection in networks is a well-studied, albeit hard, problem. Given the scale and complexity of modern day social networks, detecting “...
Yang Yang, Yizhou Sun, Saurav Pandit, Nitesh V. Ch...
A common technique for result verification in grid computing is to delegate a computation redundantly to different workers and apply majority voting to the returned results. Howe...
In this paper, we present a purely incremental, scalable algorithm for the detection of elliptical shapes in images. Our method uses an incremental version of the Random Hough Tra...
This paper presents a prototype-driven framework for classifying evolving data streams. Our framework uses cluster prototypes to summarize the data and to determine whether the cur...