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2020 – today
- 2024
[j12]Junpei Komiyama, Edouard Fouché, Junya Honda:
Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits. J. Mach. Learn. Res. 25: 112:1-112:56 (2024)- [c43]Shinji Ito, Taira Tsuchiya, Junya Honda:
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds. COLT 2024: 2522-2563 - [c42]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. COLT 2024: 3375-3430 - [c41]Taira Tsuchiya, Shinji Ito, Junya Honda:
Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring. ICML 2024 - [c40]Kazuma Shimizu, Junya Honda, Shinji Ito, Shinji Nakadai:
Learning with Posterior Sampling for Revenue Management under Time-varying Demand. IJCAI 2024: 4911-4919 - [i39]Taira Tsuchiya, Shinji Ito, Junya Honda:
Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring. CoRR abs/2402.08321 (2024) - [i38]Shinji Ito, Taira Tsuchiya, Junya Honda:
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds. CoRR abs/2403.00715 (2024) - [i37]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. CoRR abs/2403.05134 (2024) - [i36]Kazuma Shimizu, Junya Honda, Shinji Ito, Shinji Nakadai:
Learning with Posterior Sampling for Revenue Management under Time-varying Demand. CoRR abs/2405.04910 (2024) - [i35]Or Raveh, Junya Honda, Masashi Sugiyama:
Multi-Player Approaches for Dueling Bandits. CoRR abs/2405.16168 (2024) - 2023
- [c39]Jongyeong Lee, Junya Honda, Masashi Sugiyama:
Thompson Exploration with Best Challenger Rule in Best Arm Identification. ACML 2023: 646-661 - [c38]Taira Tsuchiya, Shinji Ito, Junya Honda:
Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits. AISTATS 2023: 8117-8144 - [c37]Junya Honda, Shinji Ito, Taira Tsuchiya:
Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems. ALT 2023: 726-754 - [c36]Taira Tsuchiya, Shinji Ito, Junya Honda:
Best-of-Both-Worlds Algorithms for Partial Monitoring. ALT 2023: 1484-1515 - [c35]Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama:
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits. ICML 2023: 18810-18851 - [c34]Taira Tsuchiya, Shinji Ito, Junya Honda:
Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds. NeurIPS 2023 - [i34]Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama:
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits. CoRR abs/2302.01544 (2023) - [i33]Dorian Baudry, Kazuya Suzuki, Junya Honda:
A General Recipe for the Analysis of Randomized Multi-Armed Bandit Algorithms. CoRR abs/2303.06058 (2023) - [i32]Taira Tsuchiya, Shinji Ito, Junya Honda:
Stability-penalty-adaptive Follow-the-regularized-leader: Sparsity, Game-dependency, and Best-of-both-worlds. CoRR abs/2305.17301 (2023) - [i31]Jongyeong Lee, Junya Honda, Masashi Sugiyama:
Thompson Exploration with Best Challenger Rule in Best Arm Identification. CoRR abs/2310.00539 (2023) - 2022
- [j11]Shogo Hayashi, Junya Honda, Hisashi Kashima:
Bayesian optimization with partially specified queries. Mach. Learn. 111(3): 1019-1048 (2022) - [c33]Shinji Ito, Taira Tsuchiya, Junya Honda:
Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds. COLT 2022: 1421-1422 - [c32]Shinji Ito, Taira Tsuchiya, Junya Honda:
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs. NeurIPS 2022 - [c31]Junpei Komiyama, Taira Tsuchiya, Junya Honda:
Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification. NeurIPS 2022 - [i30]Shinji Ito, Taira Tsuchiya, Junya Honda:
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs. CoRR abs/2206.00873 (2022) - [i29]Charles Riou, Junya Honda, Masashi Sugiyama:
The Survival Bandit Problem. CoRR abs/2206.03019 (2022) - [i28]Junpei Komiyama, Taira Tsuchiya, Junya Honda:
Globally Optimal Algorithms for Fixed-Budget Best Arm Identification. CoRR abs/2206.04646 (2022) - [i27]Shinji Ito, Taira Tsuchiya, Junya Honda:
Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds. CoRR abs/2206.06810 (2022) - [i26]Taira Tsuchiya, Shinji Ito, Junya Honda:
Best-of-Both-Worlds Algorithms for Partial Monitoring. CoRR abs/2207.14550 (2022) - 2021
- [c30]Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama:
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences. ICML 2021: 11637-11647 - [i25]Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama:
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences. CoRR abs/2107.08135 (2021) - [i24]Junpei Komiyama, Edouard Fouché, Junya Honda:
Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits. CoRR abs/2107.11419 (2021) - 2020
- [j10]Koji Tabata, Atsuyoshi Nakamura, Junya Honda, Tamiki Komatsuzaki:
A bad arm existence checking problem: How to utilize asymmetric problem structure? Mach. Learn. 109(2): 327-372 (2020) - [j9]Yuko Kuroki, Liyuan Xu, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama:
Polynomial-Time Algorithms for Multiple-Arm Identification with Full-Bandit Feedback. Neural Comput. 32(9): 1733-1773 (2020) - [c29]Charles Riou, Junya Honda:
Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions. ALT 2020: 777-826 - [c28]Yuko Kuroki, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama:
Online Dense Subgraph Discovery via Blurred-Graph Feedback. ICML 2020: 5522-5532 - [c27]Taira Tsuchiya, Junya Honda, Masashi Sugiyama:
Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring. NeurIPS 2020 - [i23]Masahiro Kato, Takuya Ishihara, Junya Honda, Yusuke Narita:
Adaptive Experimental Design for Efficient Treatment Effect Estimation: Randomized Allocation via Contextual Bandit Algorithm. CoRR abs/2002.05308 (2020) - [i22]Hideaki Imamura, Nontawat Charoenphakdee, Futoshi Futami, Issei Sato, Junya Honda, Masashi Sugiyama:
Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time. CoRR abs/2003.04691 (2020) - [i21]Taira Tsuchiya, Junya Honda, Masashi Sugiyama:
Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring. CoRR abs/2006.09668 (2020) - [i20]Yuko Kuroki, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama:
Online Dense Subgraph Discovery via Blurred-Graph Feedback. CoRR abs/2006.13642 (2020) - [i19]Yuko Kuroki, Junya Honda, Masashi Sugiyama:
Combinatorial Pure Exploration with Full-bandit Feedback and Beyond: Solving Combinatorial Optimization under Uncertainty with Limited Observation. CoRR abs/2012.15584 (2020)
2010 – 2019
- 2019
- [j8]Hideaki Kano, Junya Honda, Kentaro Sakamaki, Kentaro Matsuura, Atsuyoshi Nakamura, Masashi Sugiyama:
Good arm identification via bandit feedback. Mach. Learn. 108(5): 721-745 (2019) - [c26]Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, Masashi Sugiyama:
Unsupervised Domain Adaptation Based on Source-Guided Discrepancy. AAAI 2019: 4122-4129 - [c25]Liyuan Xu, Junya Honda, Masashi Sugiyama:
Dueling Bandits with Qualitative Feedback. AAAI 2019: 5549-5556 - [c24]Masahiro Kato, Takeshi Teshima, Junya Honda:
Learning from Positive and Unlabeled Data with a Selection Bias. ICLR (Poster) 2019 - [c23]Chenri Ni, Nontawat Charoenphakdee, Junya Honda, Masashi Sugiyama:
On the Calibration of Multiclass Classification with Rejection. NeurIPS 2019: 2582-2592 - [c22]Liyuan Xu, Junya Honda, Gang Niu, Masashi Sugiyama:
Uncoupled Regression from Pairwise Comparison Data. NeurIPS 2019: 3994-4004 - [i18]Chenri Ni, Nontawat Charoenphakdee, Junya Honda, Masashi Sugiyama:
On Possibility and Impossibility of Multiclass Classification with Rejection. CoRR abs/1901.10655 (2019) - [i17]Koji Tabata, Atsuyoshi Nakamura, Junya Honda, Tamiki Komatsuzaki:
A Bad Arm Existence Checking Problem. CoRR abs/1901.11200 (2019) - [i16]Yuko Kuroki, Liyuan Xu, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama:
Polynomial-time Algorithms for Combinatorial Pure Exploration with Full-bandit Feedback. CoRR abs/1902.10582 (2019) - [i15]Junya Honda:
A Note on KL-UCB+ Policy for the Stochastic Bandit. CoRR abs/1903.07839 (2019) - [i14]Liyuan Xu, Junya Honda, Gang Niu, Masashi Sugiyama:
Uncoupled Regression from Pairwise Comparison Data. CoRR abs/1905.13659 (2019) - 2018
- [c21]Liyuan Xu, Junya Honda, Masashi Sugiyama:
A fully adaptive algorithm for pure exploration in linear bandits. AISTATS 2018: 843-851 - [c20]Junpei Komiyama, Akiko Takeda, Junya Honda, Hajime Shimao:
Nonconvex Optimization for Regression with Fairness Constraints. ICML 2018: 2742-2751 - [c19]Junya Honda:
Exact Asymptotics of Random Coding Error Probability for General Memoryless Channels. ISIT 2018: 1844-1848 - [i13]Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, Masashi Sugiyama:
Unsupervised Domain Adaptation Based on Source-guided Discrepancy. CoRR abs/1809.03839 (2018) - [i12]Liyuan Xu, Junya Honda, Masashi Sugiyama:
Dueling Bandits with Qualitative Feedback. CoRR abs/1809.05274 (2018) - 2017
- [j7]Wesley Cowan, Junya Honda, Michael N. Katehakis:
Normal Bandits of Unknown Means and Variances. J. Mach. Learn. Res. 18: 154:1-154:28 (2017) - [j6]Weihua Hu, Hirosuke Yamamoto, Junya Honda:
Worst-case Redundancy of Optimal Binary AIFV Codes and Their Extended Codes. IEEE Trans. Inf. Theory 63(8): 5074-5086 (2017) - [c18]Junya Honda, Hirosuke Yamamoto:
Yariable-to-fixed length homophonie coding suitable for asymmetric channel coding. ISIT 2017: 2850-2854 - [c17]Junpei Komiyama, Junya Honda, Akiko Takeda:
Position-based Multiple-play Bandit Problem with Unknown Position Bias. NIPS 2017: 4998-5008 - [i11]Junya Honda, Hirosuke Yamamoto:
Variable-to-Fixed Length Homophonic Coding Suitable for Asymmetric Channel Coding. CoRR abs/1706.06775 (2017) - [i10]Junya Honda:
Comprehensive Analysis on Exact Asymptotics of Random Coding Error Probability. CoRR abs/1707.04401 (2017) - 2016
- [c16]Junpei Komiyama, Junya Honda, Hiroshi Nakagawa:
Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm. ICML 2016: 1235-1244 - [c15]Weihua Hu, Hirosuke Yamamoto, Junya Honda:
Tight upper bounds on the redundancy of optimal binary AIFV codes. ISIT 2016: 6-10 - [c14]Junya Honda, Hirosuke Yamamoto:
Variable-to-fixed length homophonie coding with a modified Shannon-Fano-Elias code. ISITA 2016: 11-15 - [i9]Junpei Komiyama, Junya Honda, Hiroshi Nakagawa:
Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm. CoRR abs/1605.01677 (2016) - [i8]Junya Honda, Hirosuke Yamamoto:
Variable-to-Fixed Length Homophonic Coding with a Modified Shannon-Fano-Elias Code. CoRR abs/1607.06914 (2016) - [i7]Weihua Hu, Hirosuke Yamamoto, Junya Honda:
Worst-case Redundancy of Optimal Binary AIFV Codes and their Extended Codes. CoRR abs/1607.07247 (2016) - 2015
- [j5]Junya Honda, Akimichi Takemura:
Non-asymptotic analysis of a new bandit algorithm for semi-bounded rewards. J. Mach. Learn. Res. 16: 3721-3756 (2015) - [j4]Hirosuke Yamamoto, Masato Tsuchihashi, Junya Honda:
Almost Instantaneous Fixed-to-Variable Length Codes. IEEE Trans. Inf. Theory 61(12): 6432-6443 (2015) - [c13]Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa:
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem. COLT 2015: 1141-1154 - [c12]Junpei Komiyama, Junya Honda, Hiroshi Nakagawa:
Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays. ICML 2015: 1152-1161 - [c11]Junya Honda:
Exact asymptotics for the random coding error probability. ISIT 2015: 91-95 - [c10]Runxin Wang, Junya Honda, Hirosuke Yamamoto, Rongke Liu:
FV polar coding for lossy compression with an improved exponent. ISIT 2015: 1517-1521 - [c9]Runxin Wang, Junya Honda, Hirosuke Yamamoto, Rongke Liu, Yi Hou:
Construction of polar codes for channels with memory. ITW Fall 2015: 187-191 - [c8]Junpei Komiyama, Junya Honda, Hiroshi Nakagawa:
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring. NIPS 2015: 1792-1800 - [i6]Junpei Komiyama, Junya Honda, Hiroshi Nakagawa:
Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays. CoRR abs/1506.00779 (2015) - [i5]Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa:
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem. CoRR abs/1506.02550 (2015) - [i4]Junya Honda:
Exact Asymptotics for the Random Coding Error Probability. CoRR abs/1506.03355 (2015) - [i3]Hirosuke Yamamoto, Masato Tsuchihashi, Junya Honda:
Almost Instantaneous Fix-to-Variable Length Codes. CoRR abs/1507.08733 (2015) - [i2]Junpei Komiyama, Junya Honda, Hiroshi Nakagawa:
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring. CoRR abs/1509.09011 (2015) - 2014
- [j3]Junya Honda, Hirosuke Yamamoto:
Variable Length Lossy Coding Using an LDPC Code. IEEE Trans. Inf. Theory 60(1): 762-775 (2014) - [c7]Junya Honda, Akimichi Takemura:
Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors. AISTATS 2014: 375-383 - [c6]Noboru Kunihiro, Junya Honda:
RSA Meets DPA: Recovering RSA Secret Keys from Noisy Analog Data. CHES 2014: 261-278 - [i1]Noboru Kunihiro, Junya Honda:
RSA meets DPA: Recovering RSA Secret Keys from Noisy Analog Data. IACR Cryptol. ePrint Arch. 2014: 513 (2014) - 2013
- [j2]Junya Honda, Hirosuke Yamamoto:
Polar Coding Without Alphabet Extension for Asymmetric Models. IEEE Trans. Inf. Theory 59(12): 7829-7838 (2013) - 2012
- [c5]Junya Honda, Hirosuke Yamamoto:
Polar coding without alphabet extension for asymmetric channels. ISIT 2012: 2147-2151 - [c4]Junya Honda, Hirosuke Yamamoto:
Fast Linear-Programming decoding of LDPC codes over GF(2m). ISITA 2012: 754-758 - [c3]Junya Honda, Akimichi Takemura:
Stochastic Bandit Based on Empirical Moments. AISTATS 2012: 529-537 - 2011
- [j1]Junya Honda, Akimichi Takemura:
An asymptotically optimal policy for finite support models in the multiarmed bandit problem. Mach. Learn. 85(3): 361-391 (2011) - 2010
- [c2]Junya Honda, Akimichi Takemura:
An Asymptotically Optimal Bandit Algorithm for Bounded Support Models. COLT 2010: 67-79
2000 – 2009
- 2009
- [c1]Junya Honda, Hirosuke Yamamoto:
Variable length lossy coding using an LDPC code. ISIT 2009: 1973-1977
Coauthor Index
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