In contrast to traditional machine learning algorithms, where all data are available in batch mode, the new paradigm of streaming data poses additional difficulties, since data sam...
Stream Processing Applications analyze large volumes of streaming data in real-time. These applications, consist of data sources, which produce raw streams, and processing elements...
For streaming scalably compressed video streams over unreliable networks, Limited-Retransmission Priority Encoding Transmission (LR-PET) outperforms PET remarkably since the opport...
Many algorithms have been proposed to approximate holistic aggregates, such as quantiles and heavy hitters, over data streams. However, little work has been done to explore what t...
Graham Cormode, Theodore Johnson, Flip Korn, S. Mu...
The central goal of data stream algorithms is to process massive streams of data using sublinear storage space. Motivated by work in the database community on outsourcing database...