With the sheer growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in com...
Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gon...
One of the most important challenges for the researchers in the 21st Century is related to global heating and climate change that can have as consequence the intensification of na...
Luciana A. S. Romani, Ana Maria Heuminski de &Aacu...
Identifying hot spots of moving vehicles in an urban area is essential to many smart city applications. The practical research on hot spots in smart city presents many unique feat...
Siyuan Liu, Yunhuai Liu, Lionel M. Ni, Jianping Fa...
With large amounts of correlated probabilistic data being generated in a wide range of application domains including sensor networks, information extraction, event detection etc.,...
Anomalous windows are the contiguous groupings of data points. In this paper, we propose an approach for discovering anomalous windows using Scan Statistics for Linear Intersectin...