Chance-Constrained Path Planning with Continuous Time Safety Guarantees. - Kaito Ariu; Cheng Fang; Márcio da Silva Arantes; Cláudio Toledo 001; Brian Charles Williams (AAAI Workshops, 2017)

Optimal Algorithms for Multiplayer Multi-Armed Bandits. - Po-An Wang; Alexandre Proutière; Kaito Ariu; Yassir Jedra; Alessio Russo (AISTATS, 2020)

Regret in Online Recommendation Systems. - Kaito Ariu; Narae Ryu; Se-Young Yun; Alexandre Proutière (NeurIPS, 2020)

A Practical Guide of Off-Policy Evaluation for Bandit Problems. - Masahiro Kato; Kenshi Abe; Kaito Ariu; Shota Yasui (CoRR, 2020)

The Role of Contextual Information in Best Arm Identification. - Masahiro Kato; Kaito Ariu (CoRR, 2021)

Policy Choice and Best Arm Identification: Comments on "Adaptive Treatment Assignment in Experiments for Policy Choice". - Kaito Ariu; Masahiro Kato; Junpei Komiyama; Kenichiro McAlinn (CoRR, 2021)

Optimal Simple Regret in Bayesian Best Arm Identification. - Junpei Komiyama; Kaito Ariu; Masahiro Kato; Chao Qin (CoRR, 2021)

Thresholded Lasso Bandit. - Kaito Ariu; Kenshi Abe; Alexandre Proutière (ICML, 2022)

Optimal Fixed-Budget Best Arm Identification using the Augmented Inverse Probability Weighting Estimator in Two-Armed Gaussian Bandits with Unknown Variances. - Masahiro Kato; Kaito Ariu; Masaaki Imaizumi; Masatoshi Uehara; Masahiro Nomura; Chao Qin (CoRR, 2022)

Last-Iterate Convergence with Full- and Noisy-Information Feedback in Two-Player Zero-Sum Games. - Kenshi Abe; Kaito Ariu; Mitsuki Sakamoto; Kentaro Toyoshima; Atsushi Iwasaki (CoRR, 2022)

Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games. - Kenshi Abe; Kaito Ariu; Mitsuki Sakamoto; Kentaro Toyoshima; Atsushi Iwasaki (AISTATS, 2023)

Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from Nash Equilibrium. - Yuma Fujimoto; Kaito Ariu; Kenshi Abe (IJCAI, 2023)

Exploration of Unranked Items in Safe Online Learning to Re-Rank. - Hiroaki Shiino; Kaito Ariu; Kenshi Abe; Riku Togashi (SIGIR, 2023)

Memory Asymmetry: A Key to Convergence in Zero-Sum Games. - Yuma Fujimoto; Kaito Ariu; Kenshi Abe (CoRR, 2023)

A Slingshot Approach to Learning in Monotone Games. - Kenshi Abe; Kaito Ariu; Mitsuki Sakamoto; Atsushi Iwasaki (CoRR, 2023)

Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model. - Kaito Ariu; Alexandre Proutière; Se-Young Yun (CoRR, 2023)

On Uniformly Optimal Algorithms for Best Arm Identification in Two-Armed Bandits with Fixed Budget. - Po-An Wang; Kaito Ariu; Alexandre Proutière (CoRR, 2023)

Model-Based Minimum Bayes Risk Decoding. - Yuu Jinnai; Tetsuro Morimura; Ukyo Honda; Kaito Ariu; Kenshi Abe (CoRR, 2023)

Memory Asymmetry Creates Heteroclinic Orbits to Nash Equilibrium in Learning in Zero-Sum Games. - Yuma Fujimoto; Kaito Ariu; Kenshi Abe (AAAI, 2024)

Hyperparameter-Free Approach for Faster Minimum Bayes Risk Decoding. - Yuu Jinnai; Kaito Ariu (ACL (Findings), 2024)

Filtered Direct Preference Optimization. - Tetsuro Morimura; Mitsuki Sakamoto; Yuu Jinnai; Kenshi Abe; Kaito Ariu (EMNLP, 2024)

Adaptively Perturbed Mirror Descent for Learning in Games. - Kenshi Abe; Kaito Ariu; Mitsuki Sakamoto; Atsushi Iwasaki (ICML, 2024)

Model-Based Minimum Bayes Risk Decoding for Text Generation. - Yuu Jinnai; Tetsuro Morimura; Ukyo Honda; Kaito Ariu; Kenshi Abe (ICML, 2024)

Matroid Semi-Bandits in Sublinear Time. - Ruo-Chun Tzeng; Naoto Ohsaka; Kaito Ariu (ICML, 2024)

On Universally Optimal Algorithms for A/B Testing. - Po-An Wang; Kaito Ariu; Alexandre Proutière (ICML, 2024)

Nash Equilibrium and Learning Dynamics in Three-Player Matching m-Action Games. - Yuma Fujimoto; Kaito Ariu; Kenshi Abe (CoRR, 2024)

Regularized Best-of-N Sampling to Mitigate Reward Hacking for Language Model Alignment. - Yuu Jinnai; Tetsuro Morimura; Kaito Ariu; Kenshi Abe (CoRR, 2024)

Synchronization behind Learning in Periodic Zero-Sum Games Triggers Divergence from Nash equilibrium. - Yuma Fujimoto; Kaito Ariu; Kenshi Abe (CoRR, 2024)

Last Iterate Convergence in Monotone Mean Field Games. - Noboru Isobe; Kenshi Abe; Kaito Ariu (CoRR, 2024)

Time-Varyingness in Auction Breaks Revenue Equivalence. - Yuma Fujimoto; Kaito Ariu; Kenshi Abe (CoRR, 2024)

Rate-Optimal Bayesian Simple Regret in Best Arm Identification. - Junpei Komiyama; Kaito Ariu; Masahiro Kato; Chao Qin (Math. Oper. Res., 2024)

Optimal clustering from noisy binary feedback. - Kaito Ariu; Jungseul Ok; Alexandre Proutière; Seyoung Yun (Mach. Learn., 2024)

Synchronization in Learning in Periodic Zero-Sum Games Triggers Divergence from Nash Equilibrium. - Yuma Fujimoto; Kaito Ariu; Kenshi Abe (AAAI, 2025)

Theoretical Guarantees for Minimum Bayes Risk Decoding. - Yuki Ichihara; Yuu Jinnai; Kaito Ariu; Tetsuro Morimura; Eiji Uchibe (ACL (1), 2025)

Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games. - Kenshi Abe; Mitsuki Sakamoto; Kaito Ariu; Atsushi Iwasaki (ICLR, 2025)

Global Behavior of Learning Dynamics in Zero-Sum Games with Memory Asymmetry. - Yuma Fujimoto; Kaito Ariu; Kenshi Abe (AAMAS, 2025)

Nash Equilibrium and Learning Dynamics in Three-Player Matching m-Action Games. - Yuma Fujimoto; Kaito Ariu; Kenshi Abe (AAMAS, 2025)

Regularized Best-of-N Sampling with Minimum Bayes Risk Objective for Language Model Alignment. - Yuu Jinnai; Tetsuro Morimura; Kaito Ariu; Kenshi Abe (NAACL (Long Papers), 2025)

Efficient Creative Selection in Online Advertising using Top-Two Thompson Sampling. - Daiki Katsuragawa; Yusuke Kaneko; Kaito Ariu; Kenshi Abe (WSDM, 2025)

Evaluation of Best-of-N Sampling Strategies for Language Model Alignment. - Yuki Ichihara; Yuu Jinnai; Tetsuro Morimura; Kenshi Abe; Kaito Ariu; Mitsuki Sakamoto; Eiji Uchibe (Trans. Mach. Learn. Res., 2025)

Return-Aligned Decision Transformer. - Tsunehiko Tanaka; Kenshi Abe; Kaito Ariu; Tetsuro Morimura; Edgar Simo-Serra (Trans. Mach. Learn. Res., 2025)

The Power of Perturbation under Sampling in Solving Extensive-Form Games. - Wataru Masaka; Mitsuki Sakamoto; Kenshi Abe; Kaito Ariu; Tuomas Sandholm; Atsushi Iwasaki (CoRR, 2025)

Policy Testing in Markov Decision Processes. - Kaito Ariu; Po-An Wang; Alexandre Proutière; Kenshi Abe (CoRR, 2025)