Junya Honda

1.5k citations
48 papers · 485 · h-index 12

Impact in

Papers in

Junya Honda

45 papers receiving 472 citations

Peers

Junya Honda
Comparison fields: 5 of 75
  • Computer Networks and Communications 227
  • Artificial Intelligence 232
  • Management Science and Operations Research 79
  • Sensory Systems 22
  • Computational Theory and Mathematics 47
Replace Thomas Holenstein with:
Thomas Holenstein Switzerland
Michael Tarsi Israel
Chung Chan Hong Kong
Ahmad Beirami United States
Amit Prakash India
S. Q. Zheng United States
Zaixi Zhang China
Falk Hüffner Germany
Raja Appuswamy France
Bei Chen China
Junya Honda relative to Thomas Holenstein Switzerland Thomas Holenstein's profile →
Citations per field
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Citations per year

Countries citing papers authored by Junya Honda

Since Specialization
Citations

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

Fields of papers citing papers by Junya Honda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Junya Honda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Junya Honda Line = papers co-authored together Junya Honda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013110
2
An Asymptotically Optimal Bandit Algorithm for Bounded Support Models.
201035
3 202234
4 201930
5 201529
6 201528
7
Learning from Positive and Unlabeled Data with a Selection Bias
201825
8
Nonconvex Optimization for Regression with Fairness Constraints.
201822
9 201822
10 201721
11 201111
12 201311
13 201210
14 201510
15
Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors
20148
16 20126
17 19956
18
Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions
20205
19
Position-based Multiple-play Bandit Problem with Unknown Position Bias
20175
20 20185

About Junya Honda

Junya Honda is a scholar working on Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering, Management Science and Operations Research and Molecular Biology, having authored 48 papers that have together received 485 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (15 papers), Error Correcting Code Techniques (13 papers), Advanced Wireless Communication Techniques (10 papers), Reinforcement Learning in Robotics (9 papers), Machine Learning and Algorithms (9 papers), DNA and Biological Computing (5 papers), Machine Learning and Data Classification (5 papers) and Auction Theory and Applications (5 papers). The work is most often cited by research in Computer Networks and Communications (227 citations), Artificial Intelligence (232 citations), Management Science and Operations Research (79 citations), Sensory Systems (22 citations) and Computational Theory and Mathematics (47 citations). Junya Honda has collaborated with scholars based in Japan, United States and France. Frequent co-authors include H. Yamamoto, Akimichi Takemura, Masashi Sugiyama, Weihua Hu, Masahiro Kato, Akiko Takeda, Rongke Liu, Runxin Wang, Yi Hou and Nontawat Charoenphakdee. Their work appears in journals such as Machine Learning, IEEE Transactions on Information Theory, Journal of Machine Learning Research, Tetrahedron Letters and IEEE Transactions on Magnetics.

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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