Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...
The quality of the input system model has a direct bearing on the effectiveness of the system exploration and synthesis tools. Given a well-structured system model, tools today are...
The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...
Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...
Rising interconnect delay and power consumption have motivated the investigation of alternative integrated circuit routing architectures. In particular, the X Architecture, which ...