Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
This work presents several new techniques for enhancing the performance of deterministic test pattern generation for VLSI circuits. The techniques introduced are called dynamic de...
Chen Wang, Sudhakar M. Reddy, Irith Pomeranz, Xiji...
Object recognition is challenging due to high intra-class
variability caused, e.g., by articulation, viewpoint changes,
and partial occlusion. Successful methods need to strike a...
We use the data collected by the Lung Image Database Consortium (LIDC) for modeling the radiologists’ nodule interpretations based on image content of the nodule by using decisi...
Ekarin Varutbangkul, Vesna Mitrovic, Daniela Stan ...
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...