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Publications [#313569] of Mauro Maggioni

Papers Published

  1. Maggioni, M; Minsker, S; Strawn, N, Geometric multi-resolution analysis for dictionary learning, Proceedings of SPIE - The International Society for Optical Engineering, vol. 9597 (January, 2015), ISSN 0277-786X, ISBN 9781628417630 [doi]
    (last updated on 2017/12/16)

    Abstract:
    © 2015 SPIE. We present an efficient algorithm and theory for Geometric Multi-Resolution Analysis (GMRA), a procedure for dictionary learning. Sparse dictionary learning provides the necessary complexity reduction for the critical applications of compression, regression, and classification in high-dimensional data analysis. As such, it is a critical technique in data science and it is important to have techniques that admit both efficient implementation and strong theory for large classes of theoretical models. By construction, GMRA is computationally efficient and in this paper we describe how the GMRA correctly approximates a large class of plausible models (namely, the noisy manifolds).

 

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