Junya Honda

International Conferences

Or Raveh, Junya Honda, Masashi Sugiyama, "Multi-Player Approaches for Dueling Bandits", The 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025), Phuket, Thailand, May 3-5, 2025, accepted.
Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh, "Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds", The 37th Annual Conference on Learning Theory (COLT 2024), pp.3375-3430, Edmonton, Canada, June 30 - July 3, 2024.
Shinji Ito, Taira Tsuchiya, Junya Honda, "Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Ratio Analysis and Best-of-Both-Worlds", The 37th Annual Conference on Learning Theory (COLT 2024), pp.2522-2563, Edmonton, Canada, June 30 - July 3, 2024.
Taira Tsuchiya, Shinji Ito, Junya Honda, "Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring", The 41st International Conference on Machine Learning (ICML 2024), pp.48768-48790, Vienna, Austria, July 21-27, 2024.
Kazuma Shimizu, Junya Honda, Shinji Ito, Shinji Nakadai, "Learning with Posterior Sampling for Revenue Management under Time-varying Demand", The 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024), pp.4911-4919, Jeju, Korea, Aug. 3-9, 2024. (full version)
Taira Tsuchiya, Shinji Ito, Junya Honda, "Stability-penalty-adaptive Follow-the-regularized-leader: Sparsity, Game-dependency, and Best-of-both-worlds", The 37th Neural Information Processing Systems (NeurIPS 2023), pp.47406-47437, New Orleans, USA, Dec. 10-16, 2023.
Jongyeong Lee, Junya Honda, Masashi Sugiyama, "Thompson Exploration with Best Challenger Rule in Best Arm Identification", The 15th Asian Conference on Machine Learning (ACML 2023), pp.646-661, Istanbul, Turkey, Nov. 11-14, 2023.
Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama, "Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits", The 40th International Conference on Machine Learning (ICML 2023), pp.18810-18851, Hawaii, USA, July 23-29, 2023.
Taira Tsuchiya, Shinji Ito, Junya Honda, "Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits", The 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), pp.8117-8144, Valencia, Spain, Apr. 25-27, 2023.
Junya Honda, Shinji Ito, Taira Tsuchiya, "Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems", The 34th International Conference on Algorithmic Learning Theory (ALT 2023), pp.726-754, Singapore, Feb. 20-23, 2023.
Taira Tsuchiya, Shinji Ito, Junya Honda, "Best-of-Both-Worlds Algorithms for Partial Monitoring", The 34th International Conference on Algorithmic Learning Theory (ALT 2023), pp.1484-1515, Singapore, Feb. 20-23, 2023.
Shinji Ito, Taira Tsuchiya, Junya Honda, "Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs", The 36th Neural Information Processing Systems (NeurIPS 2022), pp.28631-28643, New Orleans, USA, Dec. 28 - Nov. 4, 2022.
Junpei Komiyama, Taira Tsuchiya, Junya Honda, "Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification", The 36th Neural Information Processing Systems (NeurIPS 2022), pp.10393-10404, New Orleans, USA, Dec. 28 - Nov. 4, 2022.
Shinji Ito, Taira Tsuchiya, Junya Honda, "Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds", The 35th Annual Conference on Learning Theory (COLT 2022), pp.1421-1422, London, UK, July 2-5, 2022. (full version)
Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama, "Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences", The 38th International Conference on Machine Learning (ICML 2021), pp.11637-11647, July 18-24, 2021.
Taira Tsuchiya, Junya Honda, Masashi Sugiyama, "Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring", The 34th Neural Information Processing Systems (NeurIPS 2020), pp.8861-8871, Dec. 6-12, 2020.
Yuko Kuroki, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama, "Online Dense Subgraph Discovery via Blurred-Graph Feedback", The 37th International Conference on Machine Learning (ICML 2020), pp.5522-5532, July 13-18, 2020.
Charles Riou, Junya Honda, "Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions", The 31st International Conference on Algorithmic Learning Theory (ALT2020), pp.777-826, San Diego, USA, Feb. 8-11, 2020.
Liyuan Xu, Junya Honda, Gang Niu, Masashi Sugiyama, "Uncoupled Regression from Pairwise Comparison Data", The 33rd Neural Information Processing Systems (NeurIPS 2019), pp.3992-4002, Vancouver, Canada, Dec. 8-14, 2019.
Chenri Ni, Nontawat Charoenphakdee, Junya Honda, Masashi Sugiyama, "On the Calibration of Multiclass Classification with Rejection", The 33rd Neural Information Processing Systems (NeurIPS 2019), pp.2586-2596, Vancouver, Canada, Dec. 8-14, 2019.
Masahiro Kato, Teshima Takeshi, Junya Honda, "Learning from Positive and Unlabeled Data with a Selection Bias", The Seventh International Conference on Learning Representations (ICLR 2019), New Orleans, USA, May. 6-9, 2019.
Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, Masashi Sugiyama, "Unsupervised Domain Adaptation Based on Source-guided Discrepancy", The 23rd AAAI Conference on Artificial Intelligence (AAAI 2019), pp.5549-5556, Honolulu, USA, Jan. 27 - Feb. 1, 2019.
Liyuan Xu, Junya Honda, Masashi Sugiyama, "Dueling Bandits with Qualitative Feedback", The 23rd AAAI Conference on Artificial Intelligence (AAAI 2019), pp.4122-4129, Honolulu, USA, Jan. 27 - Feb. 1, 2019.
Junya Honda, "Exact Asymptotics of Random Coding Error Probability for General Memoryless Channels", 2018 IEEE International Symposium on Information Theory (ISIT 2018), pp.1844-1848, Vail, USA, June 17-22, 2018. (full version)
Junpei Komiyama, Akiko Takeda, Junya Honda, Hajime Shimao, "Nonconvex Optimization for Regression with Fairness Constraints", The 35th International Conference on Machine Learning (ICML 2018), pp.2737-2746, Stockholm, Sweden, July 10-15, 2018.
Liyuan Xu, Junya Honda, Masashi Sugiyama, "A fully adaptive algorithm for pure exploration in linear bandits", The 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018), pp.843-851, Canary Islands, Spain, Apr. 9-11, 2018.
Junpei Komiyama, Junya Honda, Akiko Takeda, "Position-based Multiple-play Multi-armed Bandit Problem with Unknown Position Bias", The 31st Neural Information Processing Systems (NIPS 2017), pp.5005-5015, Long Beach, USA, Dec. 4-9, 2017.
Junya Honda, Hirosuke Yamamoto, "Variable-to-fixed length homophonic coding suitable for asymmetric channel coding", 2017 IEEE International Symposium on Information Theory (ISIT 2017), pp.2860-2864, Aachen, Germany, June 25-30, 2017.
Junya Honda, Hirosuke Yamamoto, "Variable-to-Fixed Length Homophonic Coding with a Modified Shannon-Fano-Elias Code", 2016 International Symposium on Information Theory and its Applications (ISITA 2016), pp.11-15, Monterey, USA, Oct.10 - Nov.2, 2016.
Weihua Hu, Hirosuke Yamamoto, Junya Honda, "Tight Upper Bounds on the Redundancy of Optimal Binary AIFV Codes", 2016 IEEE International Symposium on Information Theory (ISIT 2016), pp.6-10, Barcelona, Spain, July 10-15, 2016.
Junpei Komiyama, Junya Honda, Hiroshi Nakagawa, "Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm", The 33rd International Conference on Machine Learning (ICML 2016), pp.1235-1244, New York, USA, June 19-24, 2016.
Junpei Komiyama, Junya Honda, Hiroshi Nakagawa, "Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring", The 29th Neural Information Processing Systems (NIPS 2015), pp.1792-1800, Montreal, Canada, Dec. 7-12, 2015.
Runxin Wang, Junya Honda, Hirosuke Yamamoto, Rongke Liu, Yi Hou, "Construction of Polar Codes for Channels with Memory", IEEE Information Theory Workshop (ITW 2015), pp.187-191, Jeju Island, Korea, Oct. 11-15, 2015.
Junpei Komiyama, Junya Honda, Hiroshi Nakagawa, "Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays", The 32nd International Conference on Machine Learning (ICML 2015), pp.1152-1161, Lille, France, July 6-11, 2015.
Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa, "Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem", The 28th Annual Conference on Learning Theory (COLT 2015), pp.1141-1154, Paris, France, July 3-6, 2015.
Junya Honda, "Exact Asymptotics for Random Coding Error Probability", 2015 IEEE International Symposium on Information Theory (ISIT 2015), pp.91-95, Hong Kong, June 14-19, 2015.
Runxin Wang, Junya Honda, Hirosuke Yamamoto, "FV Polar Coding for Lossy Compression with an Improved Exponent", 2015 IEEE International Symposium on Information Theory (ISIT 2015), pp.1517-1521, Hong Kong, June 14-19, 2015.
Noboru Kunihiro, Junya Honda, "RSA meets DPA: Recovering RSA Secret Keys from Noisy Analog Data", Workshop on Cryptographic Hardware and Embedded Systems 2014 (CHES 2014), pp.261-278, Busan, Korea, Sep. 23-26, 2014.
Junya Honda, Akimichi Takemura, "Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors", Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS 2014), pp.375-383, Reykjavik, Iceland, Apr. 22-25, 2014.
Junya Honda, Hirosuke Yamamoto, "Fast Linear-Programming Decoding of LDPC Codes over GF(2^m)", 2012 International Symposium on Information Theory and its Applications (ISITA 2012), pp.754-758, Honolulu, USA, Oct. 28-31, 2012.
Junya Honda, Hirosuke Yamamoto, "Polar Coding without Alphabet Extension for Asymmetric Channels", 2012 IEEE International Symposium on Information Theory (ISIT 2012), pp.2157-2161, Cambridge, USA, July 1-6, 2012.
Junya Honda, Akimichi Takemura, "Stochastic Bandit Based on Empirical Moments", Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2012), pp.529-537, Canary Islands, Spain, Apr. 21-23, 2012.
Junya Honda, Akimichi Takemura, "An Asymptotically Optimal Bandit Algorithm for Bounded Support Models", The 23rd Annual Conference on Learning Theory (COLT2010), pp.67-79, Haifa, Israel, June 27-29, 2010.
Junya Honda, Hirosuke Yamamoto, "Variable Length Lossy Coding using an LDPC Code", 2009 IEEE International Symposium on Information Theory (ISIT 2009), pp.1973-1977, Seoul, Korea, June 28 - July 3, 2009.
Shigeki Miyake, Junya Honda, Hirosuke Yamamoto, "Application of LCLP to Lossy Source Coding", 2008 International Symposium on Information Theory and its Applications (ISITA 2008), pp.589-594, Auckland, New Zealand, Dec. 7-10, 2008.

Journals

Charles Riou, Junya Honda, Masashi Sugiyama, "The Survival Bandit Problem", Transactions on Machine Learning Research, 2024.
Junpei Komiyama, Edouard Fouché, Junya Honda, "Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits", Journal of Machine Learning Research, vol.25(112), pp.1-56, 2024.
Kentaro Matsuura, Kentaro Sakamaki, Junya Honda, Takashi Sozu, "Optimal dose escalation methods using deep reinforcement learning in phase I oncology trials", Journal of Biopharmaceutical Statistics, vol.33, no.5, pp.639-652, Jan 2023.
Mugihiko Kato, Toshiki Okumura, Yasuhiro Tsubo, Junya Honda, Masashi Sugiyama, Kazushige Touhara, Masako Okamoto, "Spatiotemporal dynamics of odor representations in the human brain revealed by EEG decoding", Proceedings of the National Academy of Sciences (PNAS), vol.119, no.21, e2114966119, May 2022.
Shogo Hayashi, Junya Honda, Hisashi Kashima, "Bayesian optimization with partially specified queries", Machine Learning, vol.111, no.3, pp.1019-1048, Jan 2022.
Kentaro Matsuura, Junya Honda, Imad El Hanafi, Takashi Sozu, Kentaro Sakamaki, "Optimal adaptive allocation using deep reinforcement learning in a dose-response study", Statistics in Medicine, vol.41, no.7, pp.1157-1171, Mar 2022.
Kohei Shinohara, Atsuto Seko, Takashi Horiyama, Masakazu Ishihata, Junya Honda and Isao Tanaka, "Enumeration of nonequivalent substitutional structures using advanced data structure of binary decision diagram", The Journal of Chemical Physics, vol.153, no.10, pp.104-109, Sep 2020.
Yuko Kuroki, Liyuan Xu, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama, "Polynomial-time Algorithms for Multiple-arm Identification with Full-bandit Feedback", Neural Computation, vol.32, no.9, pp.1733-1773, Sep 2020.
Koji Tabata, Atsuyoshi Nakamura, Junya Honda, Tamiki Komatsuzaki, "A bad arm existence checking problem: How to utilize asymmetric problem structure?", Machine Learning, vol.109, no.2, pp.327-372, Feb 2019.
Hideaki Kano, Junya Honda, Kentaro Sakamaki, Kentaro Matsuura, Atsuyoshi Nakamura, Masashi Sugiyama, "Good Arm Identification via Bandit Feedback", Machine Learning, vol.105, no.5, pp.721-745, Mar 2019.
Wesley Cowan, Junya Honda Michael N. Katehakis, "Normal Bandits of Unknown Means and Variances", Journal of Machine Learning Research, vol.18(1), pp.5638-5665, 2017.
Kenta Kanamori, Kazuaki Toyoura, Junya Honda, Kazuki Hattori, Atsuto Seko, Masayuki Karasuyama, Kazuki Shitara, Motoki Shiga, Akihide Kuwabara, Ichiro Takeuchi, "Exploring a potential energy surface by machine learning for characterizing atomic transport", Physical Review B, vol.97, no.12 (125124), Mar 2018.
Weihua Hu, Hirosuke Yamamoto, Junya Honda, "Worst-case Redundancy of Optimal Binary AIFV Codes and Their Extended Codes", IEEE Transactions on Information Theory, vol.63, no.8, pp.5074-5086, Aug 2017.
Junya Honda, Akimichi Takemura, "Non-Asymptotic Analysis of a New Bandit Algorithm for Semi-Bounded Rewards", Journal of Machine Learning Research, vol.16, pp.3721-3756, Dec 2015.
Hirosuke Yamamoto, Masato Tsuchihashi, Junya Honda, "Almost Instantaneous Fix-to-Variable Length Codes", IEEE Transactions on Information Theory, vol.61, no.12, pp.6432-6443, Dec 2015.
Junya Honda, Hirosuke Yamamoto, "Variable Length Lossy Coding Using an LDPC Code", IEEE Transactions on Information Theory, vol.60, no.1, pp.762-775, Jan 2014.
Junya Honda, Hirosuke Yamamoto, "Polar Coding without Alphabet Extension for Asymmetric Models", IEEE Transactions on Information Theory, vol.59, no.12, pp.7829-7838, Dec 2013.
Junya Honda, Akimichi Takemura, "An Asymptotically Optimal Policy for Finite Support Models in the Multiarmed Bandit Problem", Machine Learning, vol.85, pp.361-391, Dec 2011.

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