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 ...
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
The feature selection and weighting are two important parts of automatic text classification. In this paper we give a new method based on concept attributes. We use the DEF Terms o...
A compiler approach for generating low-level computer code from high-level input for discontinuous Galerkin finite element forms is presented. The input language mirrors convention...
This paper presents our work on automatically detecting moving rigid text in digital videos. The temporal information is obtained by dividing a video frame into sub-blocks and cal...