Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Peta-scale scientific applications running on High End Computing (HEC) platforms can generate large volumes of data. For high performance storage and in order to be useful to scien...
Fang Zheng, Hasan Abbasi, Ciprian Docan, Jay F. Lo...
In recent years, the data management community has begun to consider situations in which data access is closely tied to network routing and distributed acquisition: examples includ...
Mengmeng Liu, Nicholas E. Taylor, Wenchao Zhou, Za...
Monitoring and mining real-time network data streams is crucial for managing and operating data networks. The information that network operators desire to extract from the network...
Pere Barlet-Ros, Gianluca Iannaccone, Josep Sanju&...