The problem of simultaneous feature extraction and selection, for classifier design, is considered. A new framework is proposed, based on boosting algorithms that can either 1) s...
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
The capabilities of current mobile devices, especially PDAs, are making it possible to design and develop mobile applications that employ visual techniques for using geographic da...
Internet traffic is bursty and network servers are often overloaded with surprising events or abnormal client request patterns. This paper studies a load shedding mechanism called...