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  • Search: subject:"sparse signal recovery"
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Year of publication
Subject
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high-dimensional models 4 non-sparse signal recovery 4 penalization 4 shrinkage 4 Econometrics 3 Theorie 3 Theory 3 Ökonometrie 3 Signalling 2 Mathematical programming 1 Mathematische Optimierung 1 image processing 1 nonconvex optimization 1 nonsmooth optimization 1 optimality condition 1 sparse signal recovery 1 sparse solution 1
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Online availability
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Free 4 Undetermined 1
Type of publication
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Book / Working Paper 4 Article 1
Type of publication (narrower categories)
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Working Paper 4 Arbeitspapier 2 Graue Literatur 2 Non-commercial literature 2 Article in journal 1 Aufsatz in Zeitschrift 1
Language
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English 5
Author
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Chernozhukov, Victor 4 Liao, Yuan 4 Hansen, Christian 2 Hansen, Christian Bailey 2 Fang, Shu-Cherng 1 Jiang, Shan 1 Jin, Qingwei 1
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Published in...
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CEMMAP working papers / Centre for Microdata Methods and Practice 2 cemmap working paper 2 INFORMS journal on computing : JOC 1
Source
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ECONIS (ZBW) 3 EconStor 2
Showing 1 - 5 of 5
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Sparse solutions by a quadratically constrained q (0 < q < 1) minimization model
Jiang, Shan; Fang, Shu-Cherng; Jin, Qingwei - In: INFORMS journal on computing : JOC 33 (2021) 2, pp. 511-530
Persistent link: https://www.econbiz.de/10012546104
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A lava attack on the recovery of sums of dense and sparse signals
Chernozhukov, Victor; Hansen, Christian; Liao, Yuan - 2015
Common high-dimensional methods for prediction rely on having either a sparse signal model, a model in which most parameters are zero and there are a small number of non-zero parameters that are large in magnitude, or a dense signal model, a model with no large parameters and very many small...
Persistent link: https://www.econbiz.de/10011445720
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Cover Image
A lava attack on the recovery of sums of dense and sparse signals
Chernozhukov, Victor; Hansen, Christian; Liao, Yuan - 2015
Common high-dimensional methods for prediction rely on having either a sparse signal model, a model in which most parameters are zero and there are a small number of non-zero parameters that are large in magnitude, or a dense signal model, a model with no large parameters and very many small...
Persistent link: https://www.econbiz.de/10011445767
Saved in:
Cover Image
A lava attack on the recovery sums of dense and sparse signals
Chernozhukov, Victor; Hansen, Christian Bailey; Liao, Yuan - 2015 - This version: February 10, 201
Common high-dimensional methods for prediction rely on having either a sparse signal model, a model in which most parameters are zero and there are a small number of non-zero parameters that are large in magnitude, or a dense signal model, a model with no large parameters and very many small...
Persistent link: https://www.econbiz.de/10010477564
Saved in:
Cover Image
A lava attack on the recovery of sums of dense and sparse signals
Chernozhukov, Victor; Hansen, Christian Bailey; Liao, Yuan - 2015
Common high-dimensional methods for prediction rely on having either a sparse signal model, a model in which most parameters are zero and there are a small number of non-zero parameters that are large in magnitude, or a dense signal model, a model with no large parameters and very many small...
Persistent link: https://www.econbiz.de/10011337679
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