The hierarchical hidden Markov model (HHMM) is a generalization of the hidden Markov model (HMM) that models sequences with structure at many length/time scales [FST98]. Unfortuna...
Previous stochastic approaches to generation do not include a tree-based representation of syntax. While this may be adequate or even advantageous for some applications, other app...
Abstract. The computational genome-wide annotation of gene functions requires the prediction of hierarchically structured functional classes and can be formalized as a multiclass, ...
Hierarchical graphs and clustered graphs are useful non-classical graph models for structured relational information. Hierarchical graphs are graphs with layering structures; clus...
Peter Eades, Qing-Wen Feng, Xuemin Lin, Hiroshi Na...
Performance modeling and evaluation techniques are essential when designing and implementing distributed software systems. Constructing performance models for such systems can req...
Debra L. Smarkusky, Reda A. Ammar, Imad Antonios, ...