| 2026 | COLT | Learning Periodic Strategies in Blocking Bandits Is as Hard as Bandits with Switching Costs. | Nicol Cesa-Bianchi, Junya Honda, Yuko Kuroki, Atsushi Miyauchi, Lukas Zierahn |
| 2026 | COLT | Adaptive Learning Rates with Surrogate Probability for Follow-the-Perturbed-Leader. | Jongyeong Lee, Junya Honda, Shinji Ito, Chansoo Kim |
| 2025 | AISTATS | Multi-Player Approaches for Dueling Bandits. | Or Raveh, Junya Honda, Masashi Sugiyama |
| 2025 | ICML | Geometric Resampling in Nearly Linear Time for Follow-the-Perturbed-Leader with Best-of-Both-Worlds Guarantee in Bandit Problems. | Botao Chen, Jongyeong Lee, Junya Honda |
| 2024 | COLT | Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds. | Shinji Ito, Taira Tsuchiya, Junya Honda |
| 2024 | COLT | Follow-the-Perturbed-Leader with Frchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. | Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh |
| 2024 | ICML | Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring. | Taira Tsuchiya, Shinji Ito, Junya Honda |
| 2024 | IJCAI | Learning with Posterior Sampling for Revenue Management under Time-varying Demand. | Kazuma Shimizu, Junya Honda, Shinji Ito, Shinji Nakadai |
| 2023 | ACML | Thompson Exploration with Best Challenger Rule in Best Arm Identification. | Jongyeong Lee, Junya Honda, Masashi Sugiyama |
| 2023 | AISTATS | Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits. | Taira Tsuchiya, Shinji Ito, Junya Honda |
| 2023 | ALT | Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems. | Junya Honda, Shinji Ito, Taira Tsuchiya |
| 2023 | ALT | Best-of-Both-Worlds Algorithms for Partial Monitoring. | Taira Tsuchiya, Shinji Ito, Junya Honda |
| 2023 | ICML | Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits. | Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama |
| 2022 | COLT | Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds. | Shinji Ito, Taira Tsuchiya, Junya Honda |
| 2021 | ICML | Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences. | Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama |
| 2020 | ALT | Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions. | Charles Riou, Junya Honda |
| 2020 | ICML | Online Dense Subgraph Discovery via Blurred-Graph Feedback. | Yuko Kuroki, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama |
| 2019 | AAAI | Unsupervised Domain Adaptation Based on Source-Guided Discrepancy. | Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, Masashi Sugiyama |
| 2019 | AAAI | Dueling Bandits with Qualitative Feedback. | Liyuan Xu, Junya Honda, Masashi Sugiyama |
| 2019 | ICLR | Learning from Positive and Unlabeled Data with a Selection Bias. | Masahiro Kato, Takeshi Teshima, Junya Honda |
| 2018 | AISTATS | A fully adaptive algorithm for pure exploration in linear bandits. | Liyuan Xu, Junya Honda, Masashi Sugiyama |
| 2018 | ICML | Nonconvex Optimization for Regression with Fairness Constraints. | Junpei Komiyama, Akiko Takeda, Junya Honda, Hajime Shimao |
| 2018 | ISIT | Exact Asymptotics of Random Coding Error Probability for General Memoryless Channels. | Junya Honda |
| 2017 | ISIT | Yariable-to-fixed length homophonie coding suitable for asymmetric channel coding. | Junya Honda, Hirosuke Yamamoto |
| 2016 | ICML | Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm. | Junpei Komiyama, Junya Honda, Hiroshi Nakagawa |
| 2016 | ISIT | Tight upper bounds on the redundancy of optimal binary AIFV codes. | Weihua Hu, Hirosuke Yamamoto, Junya Honda |
| 2016 | ISITA | Variable-to-fixed length homophonie coding with a modified Shannon-Fano-Elias code. | Junya Honda, Hirosuke Yamamoto |
| 2015 | COLT | Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem. | Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa |
| 2015 | ICML | Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays. | Junpei Komiyama, Junya Honda, Hiroshi Nakagawa |
| 2015 | ISIT | Exact asymptotics for the random coding error probability. | Junya Honda |
| 2015 | ISIT | FV polar coding for lossy compression with an improved exponent. | Runxin Wang, Junya Honda, Hirosuke Yamamoto, Rongke Liu |
| 2015 | ITW | Construction of polar codes for channels with memory. | Runxin Wang, Junya Honda, Hirosuke Yamamoto, Rongke Liu, Yi Hou |
| 2014 | AISTATS | Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors. | Junya Honda, Akimichi Takemura |
| 2014 | CHES | RSA Meets DPA: Recovering RSA Secret Keys from Noisy Analog Data. | Noboru Kunihiro, Junya Honda |
| 2012 | ISIT | Polar coding without alphabet extension for asymmetric channels. | Junya Honda, Hirosuke Yamamoto |
| 2012 | ISITA | Fast Linear-Programming decoding of LDPC codes over GF(2 | Junya Honda, Hirosuke Yamamoto |
| 2010 | COLT | An Asymptotically Optimal Bandit Algorithm for Bounded Support Models. | Junya Honda, Akimichi Takemura |
| 2009 | ISIT | Variable length lossy coding using an LDPC code. | Junya Honda, Hirosuke Yamamoto |