Abstract. This paper presents a probabilistic model for combining cluster ensembles utilizing information theoretic measures. Starting from a co-association matrix which summarizes...
In the real world, many optimization problems are dynamic. This requires an optimization algorithm to not only find the global optimal solution under a specific environment but als...
In this paper, we present a performance-driven softmacro clustering and placement method which preserves HDL design hierarchy to guide the soft-macro placement process. We also pr...
It is a key activity in CBD to identify high-quality components which have high cohesion and low coupling. However, component clustering is carried out in manual fashion by develop...
Existing methods for time series clustering rely on the actual data values can become impractical since the methods do not easily handle dataset with high dimensionality, missing v...