A brief survey on on-line graphics recognition is presented. We first present some common scenarios and applications of on-line graphics recognition and then identify major problem...
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
Abstract-- Due to the development of Next Generation Networks, leading to a multiservice transport layer with a multidomain environment, the importance of interconnection issues ke...
We present an integrated framework for learning asymmetric boosted classifiers and online learning to address the problem of online learning asymmetric boosted classifiers, which ...
Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data ana...