Recent Submissions

  • A Theoretical Analysis of Joint Manifolds 

    Davenport, Mark A.; Hegde, Chinmay; Duarte, Marco; Baraniuk, Richard G. (2009-01)
    The emergence of low-cost sensor architectures for diverse modalities has made it possible to deploy sensor arrays that capture a single event from a large number of vantage points and using multiple modalities. In many ...
  • Sparse Coding with Population Sketches 

    Dyer, Eva L.; Baraniuk, Richard G.; Johnson, Don H. (2009-07-13)
  • Fast, Exact Synthesis of Gaussian and nonGaussian Long-Range-Dependent Processes 

    Baraniuk, Richard; Crouse, Matthew (2009-04-15)
    1/f noise and statistically self-similar random processes such as fractional Brownian motion (fBm) and fractional Gaussian noise (fGn) are fundamental models for a host of real-world phenomena, from network traffic to ...
  • Tuning support vector machines for minimax and Neyman-Pearson classification 

    Scott, Clayton D.; Baraniuk, Richard G.; Davenport, Mark A. (2008-08-19)
    This paper studies the training of support vector machine (SVM) classifiers with respect to the minimax and Neyman-Pearson criteria. In principle, these criteria can be optimized in a straightforward way using a cost-sensitive ...
  • A simple proof of the restricted isometry property for random matrices 

    Baraniuk, Richard G.; Davenport, Mark A.; DeVore, Ronald A.; Wakin, Michael B. (2007-01-18)
    We give a simple technique for verifying the Restricted Isometry Property (as introduced by Candès and Tao) for random matrices that underlies Compressed Sensing. Our approach has two main ingredients: (i) concentration ...