We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
In this paper, we consider the clustering of resources on large scale platforms. More precisely, we target parallel applications consisting of independant tasks, where each task is...
Olivier Beaumont, Nicolas Bonichon, Philippe Ducho...
In this paper we extend the maximum spanning tree (MST) dependency parsing framework of McDonald et al. (2005c) to incorporate higher-order feature representations and allow depen...
In time-parallel simulation, the simulation time axis is decomposed into a number of slices which are assigned to parallel processes for concurrent simulation. Although a promisin...
We develop a closed-form approximation algorithm for designing IIR digital filters with linear phase and guaranteed stability. In this algorithm, the stopband and passband edge f...