Dai Ikarashi

460 total citations
15 papers, 92 citations indexed

About

Dai Ikarashi is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems. According to data from OpenAlex, Dai Ikarashi has authored 15 papers receiving a total of 92 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 6 papers in Computational Theory and Mathematics and 4 papers in Information Systems. Recurrent topics in Dai Ikarashi's work include Cryptography and Data Security (10 papers), Privacy-Preserving Technologies in Data (8 papers) and Complexity and Algorithms in Graphs (4 papers). Dai Ikarashi is often cited by papers focused on Cryptography and Data Security (10 papers), Privacy-Preserving Technologies in Data (8 papers) and Complexity and Algorithms in Graphs (4 papers). Dai Ikarashi collaborates with scholars based in Japan, Israel and United States. Dai Ikarashi's co-authors include Koki Hamada, Takeru Inoue, Osamu Akashi, Kimihiro Mizutani, Koji Chida, Ryo Kikuchi, Ryōichi Yamamoto, Benny Pinkas, Ariel Nof and Junichi Tomida and has published in prestigious journals such as Journal of the American Medical Informatics Association, Journal of Cryptology and IEEE Transactions on Network and Service Management.

In The Last Decade

Dai Ikarashi

14 papers receiving 91 citations

Peers

Dai Ikarashi

CNC

EEE

CTM

Sébastien Rouault Switzerland

Vojtěch Řehák Czechia

Aman Goel United States

Ignacio Cascudo Netherlands

Sophia Yakoubov United States

Daniel Rausch Germany

Jy-yong Sohn South Korea

Rafael G. L. D’Oliveira United States

Wenhao Yang China

Edoardo Persichetti United States

Sébastien Rouault Switzerland

Dai Ikarashi

127 ×2.8

28 ×0.7

CNC

19 ×0.8

EEE

20 ×1.1

4 ×0.5

CTM

Citations per year, relative to Dai Ikarashi Dai Ikarashi (= 1×) peers Sébastien Rouault

Countries citing papers authored by Dai Ikarashi

Since Specialization

Citations

This map shows the geographic impact of Dai Ikarashi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dai Ikarashi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dai Ikarashi more than expected).

Fields of papers citing papers by Dai Ikarashi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dai Ikarashi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dai Ikarashi. The network helps show where Dai Ikarashi may publish in the future.

Co-authorship network of co-authors of Dai Ikarashi

This figure shows the co-authorship network connecting the top 25 collaborators of Dai Ikarashi. A scholar is included among the top collaborators of Dai Ikarashi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dai Ikarashi. Dai Ikarashi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

15 of 15 papers shown

Chida, Koji, Koki Hamada, Dai Ikarashi, et al.. (2023). Fast Large-Scale Honest-Majority MPC for Malicious Adversaries. Journal of Cryptology. 36(3). 4 indexed citations

Hamada, Koki, Dai Ikarashi, Ryo Kikuchi, & Koji Chida. (2023). Efficient decision tree training with new data structure for secure multi-party computation. Proceedings on Privacy Enhancing Technologies. 2023(1). 343–364. 4 indexed citations

Asharov, Gilad, Koki Hamada, Dai Ikarashi, et al.. (2022). Efficient Secure Three-Party Sorting with Applications to Data Analysis and Heavy Hitters. Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security. 125–138. 10 indexed citations

Attrapadung, Nuttapong, Koki Hamada, Dai Ikarashi, et al.. (2022). Adam in Private: Secure and Fast Training of Deep Neural Networks with Adaptive Moment Estimation. Proceedings on Privacy Enhancing Technologies. 2022(4). 746–767. 10 indexed citations

Ikarashi, Dai, et al.. (2020). Is stateful packrat parsing really linear in practice? a counter-example, an improved grammar, and its parsing algorithms. 155–166. 1 indexed citations

Chida, Koji, Koki Hamada, Dai Ikarashi, Ryo Kikuchi, & Benny Pinkas. (2018). High-Throughput Secure AES Computation. 13–24. 4 indexed citations

Kikuchi, Ryo & Dai Ikarashi. (2018). Progress of Secure Computation: Basic Constructions and Dedicated Algorithms. IEICE ESS FUNDAMENTALS REVIEW. 12(1). 12–20. 2 indexed citations

Inoue, Takeru, et al.. (2016). Efficient Virtual Network Optimization Across Multiple Domains Without Revealing Private Information. IEEE Transactions on Network and Service Management. 13(3). 477–488. 30 indexed citations

Kikuchi, Ryo, Koji Chida, Dai Ikarashi, et al.. (2015). Secret Sharing with Share-Conversion: Achieving Small Share-Size and Extendibility to Multiparty Computation. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. E98.A(1). 213–222. 1 indexed citations

10.

Kikuchi, Ryo, Dai Ikarashi, Koki Hamada, & Koji Chida. (2015). Adaptively and Unconditionally Secure Conversion Protocols between Ramp and Linear Secret Sharing. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. E98.A(1). 223–231. 1 indexed citations

11.

Chida, Koji, et al.. (2014). Implementation and evaluation of an efficient secure computation system using 'R' for healthcare statistics. Journal of the American Medical Informatics Association. 21(e2). e326–e331. 15 indexed citations

12.

Inoue, Takeru, et al.. (2014). Efficient virtual network optimization across multiple domains without revealing private information. 3788. 1–8. 8 indexed citations

13.

Chida, Koji, et al.. (2014). R&D on Secure Computation Technology for Privacy Protection. NTT technical review. 12(7). 18–23. 1 indexed citations

14.

Kimura, Eizen, Koji Chida, Dai Ikarashi, Koki Hamada, & Ken Ishihara. (2012). Statistical Disclosure Limitation of Health Data Based on Pk-Anonymity. Studies in health technology and informatics. 180. 1117–9. 1 indexed citations

15.

Ikarashi, Dai, et al.. (2010). Modal μ-calculus on Min-plus Algebra N∞. Journal of information processing. 5(4). 1178–1192.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact