The treatment of factual data has been widely studied in different areas of Natural Language Processing (NLP). However, processing subjective information still poses important cha...
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
The primary feature of cognitive radios for wireless communication systems is the capability to optimize the relevant communication parameters given a dynamic wireless channel env...
Heuristics are widely used for solving computational intractable synthesis problems. However, until now, there has been limited effort to systematically develop heuristics that ca...
Zhiru Zhang, Yiping Fan, Miodrag Potkonjak, Jason ...