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  Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm

Gomez-Rodriguez, M., Song, L., Daneshmand, H., & Schölkopf, B. (2016). Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm. Journal of Machine Learning Research, 17(1), 3092-3120. Retrieved from dl.acm.org/citation.cfm?id=2946645.3007043.

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Gomez-Rodriguez, M.1, Author
Song, L.1, Author
Daneshmand, H.1, Author
Schölkopf, B.2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

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Free keywords: Abt. Schölkopf
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Language(s): eng - English
 Dates: 2016-01
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: GomSonDanSch16
URI: dl.acm.org/citation.cfm?id=2946645.3007043
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Title: Journal of Machine Learning Research
Source Genre: Journal
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Publ. Info: JMLR.org
Pages: - Volume / Issue: 17 (1) Sequence Number: - Start / End Page: 3092 - 3120 Identifier: ISSN: 1532-4435