山本 章人
「人生」におけるモチベーションは、"知や教養" を凌駕する、かつ独りの状態で期待される快さ・面白さに主に依存しています。'研究' の世界は私にとって、それを探るための土壌の一部です。特に、奇妙な社会や環境を前提とした (「人間であること」の根源に関わらない) "プライバシー・セキュリティ" 等の領域は私の深耕対象ではありません。個人としての究極の目標は、「人間である状態」およびそれに関わる事象の瑣末さ (あるいは重大さ) を、一定の理論的普遍性をもって示すことです。
私の夢は、『不変的な面白さ』の欠片に (ある瞬間に) 触れていることです。
Publications (夢のタネ、の一部):
Akito Yamamoto and Tetsuo Shibuya,
Differentially Private Mechanisms Using Enhanced Direction-Oriented Smooth Sensitivity,
IEEE Annual Computing and Communication Workshop and Conference (IEEE CCWC) 2026, Jan 5-7, in press. ★
Akito Yamamoto and Tetsuo Shibuya,
Direction-Oriented Smooth Sensitivity and Its Application to Genomic Statistical Analysis,
Australasian Conference on Information Security and Privacy (ACISP) 2025, Jul 14-16, pp. 63-83. [paper] [comments] ★☠️
Akito Yamamoto and Tetsuo Shibuya,
Differentially Private Selection using Smooth Sensitivity,
IEEE International Performance, Computing and Communications Conference (IEEE IPCCC) 2024, Nov 22-24, pp.1-10. [paper] [comments]
Akito Yamamoto and Tetsuo Shibuya,
Generalization and Enhancement of Piecewise Mechanism for Collecting Multidimensional Data,
IEEE International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage (IEEE SpaCCS) 2024, Oct 30-Nov 2, pp.9-18. [paper]
Akito Yamamoto and Tetsuo Shibuya,
Privacy-Optimized Randomized Response for Sharing Multi-Attribute Data,
IEEE Symposium on Computers and Communications (IEEE ISCC) 2024, Jun 26-29, pp.1-8. [paper] [comments] ★★★★
Akito Yamamoto and Tetsuo Shibuya,
A Joint Permute-and-Flip and Its Enhancement for Large-Scale Genomic Statistical Analysis,
IEEE International Conference on Data Mining Workshops (IEEE ICDMW) (TrustKDD: International Workshop on Trustworthy Knowledge Discovery and Data Mining) 2023, Dec 1-4, pp.217-226. [paper] [comments] ☠️☠️
Akito Yamamoto and Tetsuo Shibuya,
Privacy-Preserving Publication of GWAS Statistics using Smooth Sensitivity,
Annual International Conference on Privacy, Security & Trust (PST) 2023, Aug 21-23, pp.1-12. [paper] [comments]
Akito Yamamoto and Tetsuo Shibuya,
Privacy-Preserving Genomic Statistical Analysis Under Local Differential Privacy,
Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy (DBSec) 2023, Jul 19-21, pp.40-48. [paper] ☠️☠️☠️
Akito Yamamoto, Eizen Kimura, and Tetsuo Shibuya,
(ε, k)-Randomized Anonymization: ε-Differentially Private Data Sharing with k-Anonymity,
International Conference on Health Informatics (HEALTHINF) 2023, Feb 16-18, pp.287-297. [paper] [comments]
Akito Yamamoto and Tetsuo Shibuya,
Privacy-Preserving Statistical Analysis of Genomic Data using Compressive Mechanism with Haar Wavelet Transform,
Journal of Computational Biology, Volume 30, Issue 2, pp.176-188, 2023. [paper] [comments] / [workshop] [biorxiv] ★ ☠️ ?
Akito Yamamoto and Tetsuo Shibuya,
Efficient and Highly Accurate Differentially Private Statistical Genomic Analysis using Discrete Fourier Transform,
IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom) 2022, Dec 9-11, pp.525-532. [paper] [comments]
Akito Yamamoto and Tetsuo Shibuya,
Efficient Differentially Private Methods for a Transmission Disequilibrium Test in Genome Wide Association Studies,
Pacific Symposium on Biocomputing (PSB) 2022, Jan 3-7, pp.85-96. [paper]
Akito Yamamoto and Tetsuo Shibuya,
Differentially Private Linkage Analysis with TDT --- the case of two affected children per family,
IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM) 2021, Dec 9-12, pp.765-770. [paper]
Akito Yamamoto and Tetsuo Shibuya,
More practical differentially private publication of key statistics in GWAS,
Bioinformatics Advances, Volume 1, Issue 1, vbab004, 2021. [paper] [comments] ☠️
Articles:
不変的な面白さを追い求めて, 東京大学大学院理学系研究科・理学部広報誌「理学部ニュース」第55巻6号内「理学のススメ」第18回, 2024年3月, p.14. ❤︎❤︎☠️
医科研広報誌「PLATINUM STREET TIMES」Vol. 5, 2022年12月, p.3. [pdf] ❤︎
ひとりごと:
中に入るな 他人の人生を歩くな 外からの評価に邪魔されるな 無能は黙って自分と向き合え
所詮おまけの人生 何やったっていい いつ終わってもいいように 今の心に正直に