This paper aims at broadening the scope of hierarchical ATPG to the behavioral-level The main problem of using behavioral information for ATPG is the mismatch of timing models bet...
We present a docking study for Herbal, a high-level behavioral representation language based on the problem space computational model. This study docks an ACT-R model created with ...
Changkun Zhao, Jaehyon Paik, Jonathan H. Morgan, F...
We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
—This paper addresses the problem of self-validated labeling of Markov random fields (MRFs), namely to optimize an MRF with unknown number of labels. We present graduated graph c...