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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NC, IPSJ-BIO, IBISML, IPSJ-MPS (Joint) [detail] |
2015-06-23 13:00 |
Okinawa |
Okinawa Institute of Science and Technology |
Differential Privacy and Pseudo-Bayesian Posterior Kentaro Minami, Hiromi Arai, Issei Sato, Hiroshi Nakagawa (The University of Tokyo) IBISML2015-7 |
We investigate relationship between differential privacy and pseudo-Bayesian posterior distributions. Recently, Wang, et... [more] |
IBISML2015-7 pp.39-46 |
IBISML |
2013-11-12 15:45 |
Tokyo |
Tokyo Institute of Technology, Kuramae-Kaikan |
[Poster Presentation]
Query auditing for privacy preserving similarity search Hiromi Arai (RIKEN), Koji Tsuda (AIST), Jun Sakuma (Univ. of Tsukuba) IBISML2013-46 |
In this paper, we propose a query auditing method for similarity searches that examines whether database responces satis... [more] |
IBISML2013-46 pp.77-83 |
IBISML |
2012-11-07 15:30 |
Tokyo |
Bunkyo School Building, Tokyo Campus, Tsukuba Univ. |
Privacy Breach and Differential Privacy of Similarity Search Hiromi Arai (RIKEN), Jun Sakuma (Univ. of Tsukuba) IBISML2012-60 |
We examine the database privacy of similarity based ranking for a database of private records where each record and quer... [more] |
IBISML2012-60 pp.185-192 |
IBISML |
2010-11-05 15:30 |
Tokyo |
IIS, Univ. of Tokyo |
[Poster Presentation]
Privacy-preserving Semisupervised Learning on Labeled Graph Hiromi Arai, Jun Sakuma (Univ. of Tsukuba) IBISML2010-97 |
Existing label prediction methods for network data has been based on the premise that the whole net-
work structure and... [more] |
IBISML2010-97 pp.277-282 |
IBISML |
2010-06-14 16:25 |
Tokyo |
Takeda Hall, Univ. Tokyo |
Privacy Preservation in Online Prediction Jun Sakuma (Univ. of Tsukuba/JST), Hiromi Arai (U. Tsukuba) IBISML2010-9 |
In this paper, we consider online prediction from expert advice in a situation where each expert observes its own loss a... [more] |
IBISML2010-9 pp.49-56 |
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