In this paper, we present a method to estimate the number of reconfiguration steps that a time-constrained algorithm can accommodate. This analysis demonstrates how one would attac...
Many segmentation problems in medical imaging rely on accurate modeling and estimation of tissue intensity probability density functions. Gaussian mixture modeling, currently the ...
The distribution of fitness values across a set of states sharply influences the dynamics of evolutionary processes and heuristic search in combinatorial optimization. In this p...
Complete algorithms have been proposed to solve problems modelled as distributed constraint optimization (DCOP). However, there are only few attempts to address real world scenari...
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...