We present an algorithm for fast posterior inference in penalized high-dimensional state-space models, suitable in the case where a few measurements are taken in each time step. W...
In a team-based multiagent system, the ability to construct a model of an opponent team's joint behavior can be useful for determining an agent's expected distribution o...
Abstract. The functional performance model (FPM) of heterogeneous processors has proven to be more realistic than the traditional models because it integrates many important featur...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...