We present a framework for automatically summarizing social group activity over time. The problem is important in understanding large scale online social networks, which have dive...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
Ahlswede and Winter [AW02] introduced a Chernoff bound for matrix-valued random variables, which is a non-trivial generalization of the usual Chernoff bound for real-valued random...
Random walk graph and Markov chain based models are used heavily in many data and system analysis domains, including web, bioinformatics, and queuing. These models enable the desc...
While database management systems offer a comprehensive solution to data storage, they require deep knowledge of the schema, as well as the data manipulation language, in order to...