Zobrazeno 1 - 10
of 79
pro vyhledávání: '"Chohong Min"'
Autor:
Min, Chohong
Publikováno v:
Restricted to subscribing institutions.
Thesis (Ph. D.)--University of California, Los Angeles, 2004.
Vita. Includes bibliographical references (leaves 48-51).
Vita. Includes bibliographical references (leaves 48-51).
Autor:
Wonkyung Jung, Eojin Lee, Sangpyo Kim, Jongmin Kim, Namhoon Kim, Keewoo Lee, Chohong Min, Jung Hee Cheon, Jung Ho Ahn
Publikováno v:
IEEE Access, Vol 9, Pp 98772-98789 (2021)
Homomorphic Encryption (HE) has drawn significant attention as a privacy-preserving approach for cloud computing because it allows computation on encrypted messages called ciphertexts. Among the numerous HE schemes proposed thus far, HE for Arithmeti
Externí odkaz:
https://doaj.org/article/b72555b38cbf4ac4bb468b7c82235abe
Publikováno v:
IEEE Access, Vol 7, Pp 121998-122005 (2019)
This article presents a concrete mathematical analysis on Information-Theoretic Metric Learning (ITML). The analysis provides a theoretical foundation for ITML, by supplying well-posedness, strong duality, and convergence. Our analysis suggests the c
Externí odkaz:
https://doaj.org/article/3b36d08d5b714c0fa5bb64e079332e1a
Publikováno v:
Journal of Computational Physics. 488:112212
Autor:
Chohong Min, Sangpyo Kim, Nam-Hoon Kim, Jung Hee Cheon, Jung Ho Ahn, Keewoo Lee, Wonkyung Jung, Jongmin Kim, Eojin Lee
Publikováno v:
IEEE Access, Vol 9, Pp 98772-98789 (2021)
Homomorphic Encryption (HE) has drawn significant attention as a privacy-preserving approach for cloud computing because it allows computation on encrypted messages called ciphertexts. Among the numerous HE schemes proposed thus far, HE for Arithmeti
Publikováno v:
Advances in Cryptology – ASIACRYPT 2022 ISBN: 9783031229657
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::126aa4e7a1bc2264e3ab2c66b881dbc6
https://doi.org/10.1007/978-3-031-22966-4_6
https://doi.org/10.1007/978-3-031-22966-4_6
Publikováno v:
Journal of Computational Physics. 464:111324
Publikováno v:
IEEE Access, Vol 7, Pp 121998-122005 (2019)
This article presents a concrete mathematical analysis on Information-Theoretic Metric Learning (ITML). The analysis provides a theoretical foundation for ITML, by supplying well-posedness, strong duality, and convergence. Our analysis suggests the c
Autor:
Wonkyung Jung, Sangpyo Kim, Keewoo Lee, Nam-Hoon Kim, Chohong Min, Jung Hee Cheon, Eojin Lee, Jung Ho Ahn
Publikováno v:
ISPASS
Homomorphic Encryption (HE) [11] draws significant attention as a privacy-preserving way for cloud computing because it allows computation on encrypted messages called ciphertexts. Among numerous FHE schemes [2]–[4], [8], [9], HE for Arithmetic of