We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
In this paper, we investigate a new approach to process queries in data stream applications. We show that reference locality characteristics of data streams could be exploited in ...
Feifei Li, Ching Chang, George Kollios, Azer Besta...
This paper presents a trace-driven simulation study of two classes of retransmission timeout (RTO) estimators in the context of realtime streaming over the Internet. We explore th...
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
IP packet streams consist of multiple interleaving IP flows. Statistical summaries of these streams, collected for different measurement periods, are used for characterization of ...
Edith Cohen, Nick G. Duffield, Haim Kaplan, Carste...