Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divis...
To obtain correlated and complementary information contained in text mining and bibliometrics, hybrid clustering to incorporate textual content and citation information has become...
Bart De Moor, Frizo A. L. Janssens, Shi Yu, Wolfga...
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
Before an application modelled as a Directed Acyclic Graph (DAG) is executed on a heterogeneous system, a DAG mapping policy is often enacted. After mapping, the tasks (in the DAG...
Ligang He, Stephen A. Jarvis, Daniel P. Spooner, D...