NDLI: Trading approximation quality versus sparsity within incremental automatic relevance determination frameworks

Content Provider	IEEE Xplore Digital Library
Author	Shutin, D. Buchgraber, T.
Copyright Year	2012
Description	Author affiliation: Institute for Communications and Navigation, German Aerospace Center (DLR), Münchner Str. 20, 82234 Wessling Germany (Shutin, D.) \|\| Signal Processing and Speech Comm. Lab, Graz University of Technology, Inffeldgasse 16c, 8010, Austria (Buchgraber, T.)
Abstract	In this paper a trade-off between sparsity and approximation quality of models learned with incremental automatic relevance determination (IARD) is addressed. An IARD algorithm is a class of sparse Bayesian learning (SBL) schemes. It permits an intuitive and simple adjustment of estimation expressions, with the adjustment having a simple interpretation in terms of signal-to-noise ratio (SNR). This adjustment allows for implementing a trade-off between sparsity of the estimated model versus its accuracy in terms of residual mean-square error (MSE). It is found that this adjustment has a different impact on the IARD performance, depending on whether the measurement model coincides with the used estimation model or not. Specifically, in the former case the value of the adjustment parameter set to the true SNR leads to an optimum performance of the IARD with the smallest MSE and estimated signal sparsity; moreover, the estimated sparsity then coincides with the true signal sparsity. In contrast, when there is a model mismatch, the lower MSE can be achieved only at the expense of less sparser models. In this case the adjustment parameter simply trades the estimated signal sparsity versus the accuracy of the model.
Starting Page	1
Ending Page	6
File Size	176631
Page Count	6
File Format	PDF
ISBN	9781467310246
ISSN	15512541
e-ISBN	9781467310260
e-ISBN	9781467310253
DOI	10.1109/MLSP.2012.6349805
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-23
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal to noise ratio Vectors Approximation methods Estimation Noise measurement Mean square error methods
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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