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, ...
The World Wide Web (WWW) has experienced a dramatic increase in popularity since 1993. Many reports indicate that its growth will continue at an exponential rate. This growth has ...
It is widely accepted that the use of more compact representations than lookup tables is crucial to scaling reinforcement learning (RL) algorithms to real-world problems. Unfortun...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
With the increasing functionality and complexity of distributed systems, resource failures are inevitable. While numerous models and algorithms for dealing with failures exist, th...
Derrick Kondo, Bahman Javadi, Alexandru Iosup, Dic...
We have developed a system architecture, measuring and modeling techniques, and algorithms for on-line power and energy optimization and thermal management. The starting point for...