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, ...
Users of MapReduce often run into performance problems when they scale up their workloads. Many of the problems they encounter can be overcome by applying techniques learned from ...
Avrilia Floratou, Jignesh M. Patel, Eugene J. Shek...
— Recent research has shown that interference can make a significant impact on the performance of multihop wireless networks. Researchers have studied interference-aware topolog...
Jian Tang, Guoliang Xue, Christopher Chandler, Wei...
Task to resource mapping problems are encountered during (i) hardware-software co-design and (ii) performance optimization of Network Processor systems. The goal of the first pro...
Liang Yang, Tushar Gohad, Pavel Ghosh, Devesh Sinh...
As more and more physical information becomes available, a critical problem is enabling the simple and efficient exchange of this data. We present our design for a simple RESTful ...
Stephen Dawson-Haggerty, Xiaofan Jiang, Gilman Tol...