Title:
PRIVATE EXPONENT TRANSFORMATION DEVICE, PRIVATE EXPONENT TRANSFORMATION METHOD, AND PROGRAM
Document Type and Number:
WIPO Patent Application WO/2022/259489
Kind Code:
A1
Abstract:
A private exponent transformation device according to one embodiment transforms data through a Box–Cox transformation and includes: a random number generation unit that generates random numbers λ− and λ+ satisfying λ− < 0 and λ+ > 0, respectively, as the initial values of the parameter of the Box–Cox transformation; an optimization unit that uses the data to calculate respective local solutions λ−^ and λ+^ of the parameter of the Box–Cox transformation through differentially private gradient descent that treats each of λ− and λ+ as initial values; a parameter output unit that outputs one of the local solutions λ−^ or λ+^ as the optimum solution of the parameter; and a transformation unit that transforms the data through the Box–Cox transformation using the optimum solution.
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Inventors:
HASEGAWA SATOSHI (JP)
MIURA TAKAYUKI (JP)
MIURA TAKAYUKI (JP)
Application Number:
PCT/JP2021/022205
Publication Date:
December 15, 2022
Filing Date:
June 10, 2021
Export Citation:
Assignee:
NIPPON TELEGRAPH & TELEPHONE (JP)
International Classes:
G06F17/18
Other References:
MART\IN ABADI; ANDY CHU; IAN GOODFELLOW; H. BRENDAN MCMAHAN; ILYA MIRONOV; KUNAL TALWAR; LI ZHANG: "Deep Learning with Differential Privacy", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 1 July 2016 (2016-07-01), 201 Olin Library Cornell University Ithaca, NY 14853 , XP081396507, DOI: 10.1145/2976749.2978318
"Feature Engineering for Machine Learning: Principles and Practice with Python (1st edition) ", 25 February 2019, O'REILLY, JP, ISBN: 978-4-87311-868-0, article ZHENG, ALICE: "Section 2.3.2.", pages: 24 - 29, XP009542571
VENUGOPAL ROHIT; SHAFQAT NOMAN; VENUGOPAL ISHWAR; TILLBURY BENJAMIN MARK JOHN; STAFFORD HARRY DEMETRIOS; BOURAZERI AIKATERINI: "Privacy preserving Generative Adversarial Networks to model Electronic Health Records", NEURAL NETWORKS., ELSEVIER SCIENCE PUBLISHERS, BARKING., GB, vol. 153, 25 June 2022 (2022-06-25), GB , pages 339 - 348, XP087131088, ISSN: 0893-6080, DOI: 10.1016/j.neunet.2022.06.022
"Feature Engineering for Machine Learning: Principles and Practice with Python (1st edition) ", 25 February 2019, O'REILLY, JP, ISBN: 978-4-87311-868-0, article ZHENG, ALICE: "Section 2.3.2.", pages: 24 - 29, XP009542571
VENUGOPAL ROHIT; SHAFQAT NOMAN; VENUGOPAL ISHWAR; TILLBURY BENJAMIN MARK JOHN; STAFFORD HARRY DEMETRIOS; BOURAZERI AIKATERINI: "Privacy preserving Generative Adversarial Networks to model Electronic Health Records", NEURAL NETWORKS., ELSEVIER SCIENCE PUBLISHERS, BARKING., GB, vol. 153, 25 June 2022 (2022-06-25), GB , pages 339 - 348, XP087131088, ISSN: 0893-6080, DOI: 10.1016/j.neunet.2022.06.022
Attorney, Agent or Firm:
ITOH, Tadashige et al. (JP)
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