Naoto Ohsaka
- Statistical and Nonlinear Physics top 5%
- Computer Networks and Communications top 10%
- Artificial Intelligence top 10%
- Information Systems
- Computer Vision and Pattern Recognition
- Co-authors
- Ken‐ichi KawarabayashiYuichi YoshidaTakuya AkibaTakanori MaeharaTomohiro SonobeSumio FujitaAlex ThomoYoichi Iwata
- Topics
- Complexity and Algorithms in Graphs (7 papers)Complex Network Analysis Techniques (6 papers)Optimization and Search Problems (4 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputational MathematicsComputer Networks and Communications
In The Last Decade
Naoto Ohsaka
15 papers receiving 293 citations
Peers
Comparison fields: 5 of 40
- Statistical and Nonlinear Physics 225
- Computer Networks and Communications 102
- Artificial Intelligence 98
- Information Systems 43
- Computer Vision and Pattern Recognition 42
Countries citing papers authored by Naoto Ohsaka
This map shows the geographic impact of Naoto Ohsaka'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 Naoto Ohsaka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Naoto Ohsaka more than expected).
Fields of papers citing papers by Naoto Ohsaka
This network shows the impact of papers produced by Naoto Ohsaka. 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 Naoto Ohsaka. The network helps show where Naoto Ohsaka may publish in the future.
Co-authorship network of co-authors of Naoto Ohsaka
This figure shows the co-authorship network connecting the top 25 collaborators of Naoto Ohsaka. A scholar is included among the top collaborators of Naoto Ohsaka 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 Naoto Ohsaka. Naoto Ohsaka is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | Tracking Regret Bounds for Online Submodular Optimization | 2 |
| 10 | Unconstrained MAP Inference, Exponentiated Determinantal Point Processes, and Exponential Inapproximability. | 1 |
| 11 | 0 | |
| 12 | On the (In)tractability of Computing Normalizing Constants for the Product of Determinantal Point Processes | 1 |
| 13 | 4 | |
| 14 | 5 | |
| 15 | 11 | |
| 16 | 26 | |
| 17 | 57 | |
| 18 | Monotone k -submodular function maximization with size constraints | 15 |
| 19 | 40 | |
| 20 | 131 |
About Naoto Ohsaka
Naoto Ohsaka is a scholar working on Computational Theory and Mathematics, Statistical and Nonlinear Physics and Statistics and Probability, having authored 21 papers that have together received 301 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (7 papers), Complex Network Analysis Techniques (6 papers) and Optimization and Search Problems (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (225 citations), Computational Mathematics (3 citations) and Computer Networks and Communications (102 citations). Naoto Ohsaka has collaborated with scholars based in Japan and Canada. Frequent co-authors include Ken‐ichi Kawarabayashi, Yuichi Yoshida, Takuya Akiba, Takanori Maehara, Tomohiro Sonobe, Sumio Fujita, Alex Thomo and Yoichi Iwata. Their work appears in journals such as Proceedings of the VLDB Endowment, Journal of Artificial Intelligence Research and Operations Research Letters.
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.