Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
Cluster tools play an important role in modern semiconductor fabs. Due to their complexity in configuration and their varying material flow, the creation of accurate throughput mo...
Jan Lange, Kilian Schmidt, Roy Borner, Oliver Rose
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
—In order to meet the increasing demands of present and upcoming data-intensive computer applications, there has been a major shift in the disk subsystem, which now consists of m...
Rajat Garg, Seung Woo Son, Mahmut T. Kandemir, Pad...
Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...