In situations where Bayesian networks (BN) inferencing approximation is allowable, we show how to reduce the amount of sensory observations necessary and in a multi-agent context ...
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...
This study proposes a methodology to infer maximum air temperature from space using observations from polar orbiting satellite MODIS. A previous study showed that minimum Land Sur...
Pietro Ceccato, Christelle Vancutsem, Marouane Tem...
Several activities in service oriented computing can benefit from knowing ahead of time future properties of a given service composition. In this paper we focus on how statically i...
Dragan Ivanovic, Manuel Carro, Manuel V. Hermenegi...