Ensemble learning is a variational Bayesian method in which an intractable distribution is approximated by a lower-bound. Ensemble learning results in models with better generaliz...
Graph structure can model the relationships among a set of objects. Mining quasi-clique patterns from large dense graph data makes sense with respect to both statistic and applica...
SIMD (single instruction multiple data)-type processors have been found very efficient in image processing applications, because their repetitive structure is able to exploit the...
Raymond Frijns, Hamed Fatemi, Bart Mesman, Henk Co...
Identifying and inferring performances of a network topology is a well known problem. Achieving this by using only end-to-end measurements at the application level is a method kno...
In this paper we consider parity games defined by higher-order pushdown automata. These automata generalise pushdown automata by the use of higher-order stacks, which are nested ...
Arnaud Carayol, Matthew Hague, Antoine Meyer, C.-H...