Shotaro Akaho

3.2k total citations
100 papers, 981 citations indexed

About

Shotaro Akaho is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shotaro Akaho has authored 100 papers receiving a total of 981 indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Artificial Intelligence, 21 papers in Signal Processing and 20 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shotaro Akaho's work include Neural Networks and Applications (20 papers), Blind Source Separation Techniques (13 papers) and Recommender Systems and Techniques (10 papers). Shotaro Akaho is often cited by papers focused on Neural Networks and Applications (20 papers), Blind Source Separation Techniques (13 papers) and Recommender Systems and Techniques (10 papers). Shotaro Akaho collaborates with scholars based in Japan, United States and United Kingdom. Shotaro Akaho's co-authors include Toshihiro Kamishima, Jun Sakuma, Hideki Asoh, Masahiro Hamasaki, Satoru Hayamizu, Isao Hara, Toshihiro Matsui, Шун-ичи Амари, Yoichi Motomura and Hideitsu Hino and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Chemical Geology.

In The Last Decade

Shotaro Akaho

89 papers receiving 908 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shotaro Akaho Japan 15 510 204 156 135 122 100 981
Wenbin Zhang United States 19 607 1.2× 133 0.7× 214 1.4× 127 0.9× 154 1.3× 139 1.5k
Matt J. Kusner United States 14 1.1k 2.1× 316 1.5× 246 1.6× 72 0.5× 65 0.5× 26 1.7k
Been Kim United States 15 1.1k 2.1× 280 1.4× 74 0.5× 62 0.5× 117 1.0× 32 1.5k
Matthew Graham United Kingdom 2 930 1.8× 254 1.2× 151 1.0× 84 0.6× 23 0.2× 2 1.5k
Karthikeyan Natesan Ramamurthy United States 17 667 1.3× 469 2.3× 106 0.7× 102 0.8× 463 3.8× 102 1.7k
Wojciech Marian Czarnecki Poland 15 827 1.6× 285 1.4× 53 0.3× 46 0.3× 40 0.3× 36 1.5k
Max Chickering United States 11 1.1k 2.1× 241 1.2× 430 2.8× 135 1.0× 28 0.2× 18 1.7k
Andrea Danyluk United States 11 640 1.3× 277 1.4× 172 1.1× 85 0.6× 11 0.1× 31 1.3k
Anand D. Sarwate United States 22 1.3k 2.6× 159 0.8× 111 0.7× 91 0.7× 37 0.3× 119 2.5k
Michael J. Quinn United States 19 354 0.7× 111 0.5× 233 1.5× 85 0.6× 21 0.2× 71 1.8k

Countries citing papers authored by Shotaro Akaho

Since Specialization
Citations

This map shows the geographic impact of Shotaro Akaho'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 Shotaro Akaho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shotaro Akaho more than expected).

Fields of papers citing papers by Shotaro Akaho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shotaro Akaho. 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 Shotaro Akaho. The network helps show where Shotaro Akaho may publish in the future.

Co-authorship network of co-authors of Shotaro Akaho

This figure shows the co-authorship network connecting the top 25 collaborators of Shotaro Akaho. A scholar is included among the top collaborators of Shotaro Akaho 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 Shotaro Akaho. Shotaro Akaho is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Itano, Keita, Kohei Fukuda, N. T. Kita, et al.. (2025). Evaluation of Matrix Effects in SIMS Using Gaussian Process Regression: The Case of Olivine Mg Isotope Microanalysis. Rapid Communications in Mass Spectrometry. 39(13). e10038–e10038.
2.
Matsumura, Tarojiro, Naoka Nagamura, Shotaro Akaho, Kenji Nagata, & Yasunobu Ando. (2024). Maximum a posteriori estimation for high-throughput peak fitting in X-ray photoelectron spectroscopy. SHILAP Revista de lepidopterología. 4(1).
3.
Matsumura, Tarojiro, Naoka Nagamura, Shotaro Akaho, Kenji Nagata, & Yasunobu Ando. (2023). High-throughput XPS spectrum modeling with autonomous background subtraction for 3 d 5/2 peak mapping of SnS. SHILAP Revista de lepidopterología. 3(1). 5 indexed citations
5.
Matsumura, Tarojiro, Naoka Nagamura, Shotaro Akaho, Kenji Nagata, & Yasunobu Ando. (2021). Spectrum adapted expectation-conditional maximization algorithm for extending high–throughput peak separation method in XPS analysis. SHILAP Revista de lepidopterología. 1(1). 45–55. 7 indexed citations
6.
Matsumura, Tarojiro, Naoka Nagamura, Shotaro Akaho, Kenji Nagata, & Yasunobu Ando. (2019). Spectrum adapted expectation-maximization algorithm for high-throughput peak shift analysis. Science and Technology of Advanced Materials. 20(1). 733–745. 19 indexed citations
7.
Karakida, Ryo, Shotaro Akaho, & Шун-ичи Амари. (2018). Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach. International Conference on Artificial Intelligence and Statistics. 1032–1041. 1 indexed citations
8.
Akaho, Shotaro, et al.. (2014). Basis Functions for Fast Learning of Log-linear Models. IEICE Technical Report; IEICE Tech. Rep.. 114(306). 307–312.
9.
Kamishima, Toshihiro, Shotaro Akaho, Hideki Asoh, & Jun Sakuma. (2014). Correcting Popularity Bias by Enhancing Recommendation Neutrality.. Conference on Recommender Systems. 31 indexed citations
10.
Kamishima, Toshihiro, et al.. (2013). Analysis of Medical Treatment Data using Inverse Reinforcement Learning. IEICE Technical Report; IEICE Tech. Rep.. 112(390). 13–17. 1 indexed citations
11.
Kamishima, Toshihiro, Shotaro Akaho, Hideki Asoh, & Jun Sakuma. (2013). Efficiency Improvement of Neutrality-Enhanced Recommendation.. Conference on Recommender Systems. 1–8. 17 indexed citations
12.
Kamishima, Toshihiro, Shotaro Akaho, Hideki Asoh, & Jun Sakuma. (2012). Enhancement of the Neutrality in Recommendation.. Conference on Recommender Systems. 8–14. 23 indexed citations
13.
Géczy, Peter, Noriaki Izumi, Shotaro Akaho, & Kôiti Hasida. (2007). HUMAN WEB BEHAVIOR MINING. 2 indexed citations
14.
Géczy, Peter, Noriaki Izumi, Shotaro Akaho, & Kôiti Hasida. (2006). Navigation Space Formalism and Exploration of Knowledge Worker Behavior on Intranet. 20(1). 163–172.
15.
Géczy, Peter, Shotaro Akaho, & Shiro Usui. (2006). Efficient First Order Superlinear Algorithms.. 1 indexed citations
16.
Akaho, Shotaro, et al.. (2006). Riemannian Optimization Method on Generalized Flag Manifolds for Complex and Subspace ICA. AIP conference proceedings. 872. 89–96. 3 indexed citations
17.
Kamishima, Toshihiro, Hideto Kazawa, & Shotaro Akaho. (2004). Estimating Attributed Central Orders: An Empirical Comparison.. 563–565. 2 indexed citations
18.
Akaho, Shotaro & Toshihiro Kamishima. (2002). A Statistical Approach for Learning from Order Examples by Linear Models. 181–181. 1 indexed citations
19.
Akaho, Shotaro, et al.. (1998). Pursuit Movement of Pan-Tilt Camera by Feedback-Error-Learning. International Conference on Neural Information Processing. 409–412. 1 indexed citations
20.
Asoh, Hideki, Satoru Hayamizu, Isao Hara, et al.. (1997). Socially embedded learning of the office-conversant mobile robot Jijo-2. International Joint Conference on Artificial Intelligence. 2. 880–885. 68 indexed citations

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.

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