Junya Honda

Edouard Fouché

J. Mach. Learn. Res., 2024

Multi-Player Approaches for Dueling Bandits.

[BibT_eX]

[DOI]

Or Raveh

CoRR, 2024

Learning with Posterior Sampling for Revenue Management under Time-varying Demand.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds.

[BibT_eX]

[DOI]

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds.

[BibT_eX]

[DOI]

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

A General Recipe for the Analysis of Randomized Multi-Armed Bandit Algorithms.

[BibT_eX]

[DOI]

Dorian Baudry

Kazuya Suzuki

CoRR, 2023

Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Best-of-Both-Worlds Algorithms for Partial Monitoring.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Thompson Exploration with Best Challenger Rule in Best Arm Identification.

[BibT_eX]

[DOI]

Jongyeong Lee

Proceedings of the Asian Conference on Machine Learning, 2023

2022

Bayesian optimization with partially specified queries.

[BibT_eX]

[DOI]

Shogo Hayashi

Hisashi Kashima

Mach. Learn., 2022

Globally Optimal Algorithms for Fixed-Budget Best Arm Identification.

[BibT_eX]

[DOI]

CoRR, 2022

The Survival Bandit Problem.

[BibT_eX]

[DOI]

Charles Riou

CoRR, 2022

Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Polynomial-Time Algorithms for Multiple-Arm Identification with Full-Bandit Feedback.

[BibT_eX]

[DOI]

Neural Comput., 2020

A bad arm existence checking problem: How to utilize asymmetric problem structure?

[BibT_eX]

[DOI]

Mach. Learn., 2020

Combinatorial Pure Exploration with Full-bandit Feedback and Beyond: Solving Combinatorial Optimization under Uncertainty with Limited Observation.

[BibT_eX]

[DOI]

Yuko Kuroki

CoRR, 2020

Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time.

[BibT_eX]

[DOI]

Hideaki Imamura

CoRR, 2020

Adaptive Experimental Design for Efficient Treatment Effect Estimation: Randomized Allocation via Contextual Bandit Algorithm.

[BibT_eX]

[DOI]

CoRR, 2020

Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Dense Subgraph Discovery via Blurred-Graph Feedback.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions.

[BibT_eX]

[DOI]

Charles Riou

Proceedings of the Algorithmic Learning Theory, 2020

2019

Good arm identification via bandit feedback.

[BibT_eX]

[DOI]

Mach. Learn., 2019

A Note on KL-UCB+ Policy for the Stochastic Bandit.

[BibT_eX]

[DOI]

CoRR, 2019

Polynomial-time Algorithms for Combinatorial Pure Exploration with Full-bandit Feedback.

[BibT_eX]

[DOI]

CoRR, 2019

A Bad Arm Existence Checking Problem.

[BibT_eX]

[DOI]

CoRR, 2019

On Possibility and Impossibility of Multiclass Classification with Rejection.

[BibT_eX]

[DOI]

Chenri Ni

CoRR, 2019

Uncoupled Regression from Pairwise Comparison Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On the Calibration of Multiclass Classification with Rejection.

[BibT_eX]

[DOI]

Chenri Ni

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning from Positive and Unlabeled Data with a Selection Bias.

[BibT_eX]

[DOI]

Masahiro Kato

Takeshi Teshima

Proceedings of the 7th International Conference on Learning Representations, 2019

Dueling Bandits with Qualitative Feedback.

[BibT_eX]

[DOI]

Liyuan Xu

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Unsupervised Domain Adaptation Based on Source-Guided Discrepancy.

[BibT_eX]

[DOI]

Seiichi Kuroki

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Exact Asymptotics of Random Coding Error Probability for General Memoryless Channels.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Nonconvex Optimization for Regression with Fairness Constraints.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

A fully adaptive algorithm for pure exploration in linear bandits.

[BibT_eX]

[DOI]

Liyuan Xu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Worst-case Redundancy of Optimal Binary AIFV Codes and Their Extended Codes.

[BibT_eX]

[DOI]

Weihua Hu

IEEE Trans. Inf. Theory, 2017

Normal Bandits of Unknown Means and Variances.

[BibT_eX]

[DOI]

Wesley Cowan

Michael N. Katehakis

J. Mach. Learn. Res., 2017

Variable-to-Fixed Length Homophonic Coding Suitable for Asymmetric Channel Coding.

[BibT_eX]

[DOI]

CoRR, 2017

Comprehensive Analysis on Exact Asymptotics of Random Coding Error Probability.

[BibT_eX]

[DOI]

CoRR, 2017

Position-based Multiple-play Bandit Problem with Unknown Position Bias.

[BibT_eX]

[DOI]

Akiko Takeda

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Yariable-to-fixed length homophonie coding suitable for asymmetric channel coding.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

2016

Variable-to-Fixed Length Homophonic Coding with a Modified Shannon-Fano-Elias Code.

[BibT_eX]

[DOI]

CoRR, 2016

Variable-to-fixed length homophonie coding with a modified Shannon-Fano-Elias code.

[BibT_eX]

[DOI]

Proceedings of the 2016 International Symposium on Information Theory and Its Applications, 2016

Tight upper bounds on the redundancy of optimal binary AIFV codes.

[BibT_eX]

[DOI]

Weihua Hu

Proceedings of the IEEE International Symposium on Information Theory, 2016

Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm.

[BibT_eX]

[DOI]

Hiroshi Nakagawa

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Almost Instantaneous Fixed-to-Variable Length Codes.

[BibT_eX]

[DOI]

Masato Tsuchihashi

IEEE Trans. Inf. Theory, 2015

Non-asymptotic analysis of a new bandit algorithm for semi-bounded rewards.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2015

Almost Instantaneous Fix-to-Variable Length Codes.

[BibT_eX]

[DOI]

Masato Tsuchihashi

CoRR, 2015

Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring.

[BibT_eX]

[DOI]

Hiroshi Nakagawa

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Construction of polar codes for channels with memory.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE Information Theory Workshop, 2015

FV polar coding for lossy compression with an improved exponent.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2015

Exact asymptotics for the random coding error probability.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2015

Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays.

[BibT_eX]

[DOI]

Hiroshi Nakagawa

Proceedings of the 32nd International Conference on Machine Learning, 2015

Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem.

[BibT_eX]

[DOI]

Proceedings of The 28th Conference on Learning Theory, 2015

2014

Variable Length Lossy Coding Using an LDPC Code.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2014

RSA meets DPA: Recovering RSA Secret Keys from Noisy Analog Data.

[BibT_eX]

[DOI]

Noboru Kunihiro

IACR Cryptol. ePrint Arch., 2014

Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors.

[BibT_eX]

[DOI]

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Polar Coding Without Alphabet Extension for Asymmetric Models.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2013

2012

Stochastic Bandit Based on Empirical Moments.

[BibT_eX]

[DOI]

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Fast Linear-Programming decoding of LDPC codes over GF(2<sup>m</sup>).

[BibT_eX]

[DOI]

Proceedings of the International Symposium on Information Theory and its Applications, 2012

Polar coding without alphabet extension for asymmetric channels.

[BibT_eX]

[DOI]

Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

2011

An asymptotically optimal policy for finite support models in the multiarmed bandit problem.

[BibT_eX]

[DOI]

Mach. Learn., 2011

2010

An Asymptotically Optimal Bandit Algorithm for Bounded Support Models.

[BibT_eX]

[DOI]