Publications [#338851] of Lawrence Carin

Papers Published

1. Zhou, M; Paisley, J; Carin, L, Nonparametric learning of dictionaries for sparse representation of sensor signals, CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (December, 2009), pp. 237-240, IEEE [doi]
   (last updated on 2024/12/31)

   Abstract:
   Nonparametric Bayesian techniques are considered for learning dictionaries for sparse data representations, with applications in sparse rendering of sensor data. The beta process is employed as a prior for learning the dictionary, and this non parametric method naturally infers an appropriate dictionary size. The proposed method can learn a sparse dictionary, and may also be used to denoise a signal under test. The noise variance need not be known, and can be non-stationary. The dictionary coefficients for a given sensor signal may be employed within a classifier. Several exam pIe results are presented, using both Gibbs and variational Bayesian inference, with comparisons to other state-of-the-art approaches. © 2009 IEEE.