We present a novel discriminative training algorithm for n-gram language models for use in large vocabulary continuous speech recognition. The algorithm uses large margin estimati...
Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van H...
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
This report presents a model-driven, stress test methodology aimed at increasing chances of discovering faults related to network traffic in Distributed Real-Time Systems (DRTS). T...
— As part of a program to find methods of reducing spatial interference in multi-robot systems, we propose the Interaction Grid (IG), a generalization of the Occupancy Grid that...