We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
Abstract-- Traditional methods of spoken utterance classification (SUC) adopt two independently trained phases. In the first phase, an automatic speech recognition (ASR) module ret...
Sibel Yaman, Li Deng, Dong Yu, Ye-Yi Wang, Alex Ac...
Algorithms for classification of 3D objects either recover the depth information lost during imaging using multiple images, structured lighting, image cues, etc. or work directly t...
Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated wi...
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 ...