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  Hermite Polynomial Features for Private Data Generation

Vinaroz, M., Charusaie, M.-A., Harder, F., Adamczewski, K., & Park, M. J. (2022). Hermite Polynomial Features for Private Data Generation. In K. Chaudhuri, S. Jegelka, L. Song, C. Szepesvari, G. Niu, & S. Sabato (Eds.), Proceedings of the 39th International Conference on Machine Learning (ICML 2022) (pp. 22300-22324). PMLR. Retrieved from https://proceedings.mlr.press/v162/vinaroz22a.html.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0010-2F7E-E Version Permalink: https://hdl.handle.net/21.11116/0000-0010-2F7F-D
Genre: Conference Paper

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Locator:
https://proceedings.mlr.press/v162/vinaroz22a.html (Publisher version)
Description:
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OA-Status:
Miscellaneous
Locator:
https://doi.org/10.48550/arXiv.2106.05042 (Preprint)
Description:
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OA-Status:
Green

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 Creators:
Vinaroz , Margarita1, Author
Charusaie , Mohammad-Amin1, Author
Harder, Frederik1, Author           
Adamczewski, Kamil1, Author           
Park, Mi Jung2, Author
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              
2External Organizations, ou_persistent22              

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Free keywords: Abt. Schölkopf
 Abstract: -

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Language(s): eng - English
 Dates: 2022
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: hermite22
URI: https://proceedings.mlr.press/v162/vinaroz22a.html
arXiv: 2106.05042
 Degree: -

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Title: 39th International Conference on Machine Learning (ICML 2022)
Place of Event: Baltimore, MD
Start-/End Date: 2022-07-17 - 2022-07-23

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Source 1

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Title: Proceedings of the 39th International Conference on Machine Learning (ICML 2022)
Source Genre: Proceedings
 Creator(s):
Chaudhuri, Kamalika 1, Editor
Jegelka, Stefanie 1, Editor
Song, Le1, Editor
Szepesvari, Csaba 1, Editor
Niu, Gang1, Editor
Sabato, Sivan1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: PMLR
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 22300 - 22324 Identifier: URI: https://proceedings.mlr.press/v162/

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Title: Proceedings of Machine Learning Research
  Abbreviation : PMLR
Source Genre: Series
 Creator(s):
Affiliations:
Publ. Info: PMLR
Pages: - Volume / Issue: 162 Sequence Number: - Start / End Page: - Identifier: URI: https://proceedings.mlr.press
ISSN: 2640-3498