Kaito Ariu

According to our database, Kaito Ariu authored at least 34 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Optimal clustering from noisy binary feedback.

Kaito Ariu, Jungseul Ok, Alexandre Proutière, Seyoung Yun

Mach. Learn., May, 2024

Rate-Optimal Bayesian Simple Regret in Best Arm Identification.

Junpei Komiyama, Kaito Ariu, Masahiro Kato, Chao Qin

Math. Oper. Res., 2024

Last Iterate Convergence in Monotone Mean Field Games.

Noboru Isobe, Kenshi Abe, Kaito Ariu

CoRR, 2024

Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games.

Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu, Atsushi Iwasaki

CoRR, 2024

Synchronization behind Learning in Periodic Zero-Sum Games Triggers Divergence from Nash equilibrium.

Yuma Fujimoto, Kaito Ariu, Kenshi Abe

CoRR, 2024

Global Behavior of Learning Dynamics in Zero-Sum Games with Memory Asymmetry.

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

Nash Equilibrium and Learning Dynamics in Three-Player Matching m-Action Games.

Yuma Fujimoto, Kaito Ariu, Kenshi Abe

CoRR, 2024

Return-Aligned Decision Transformer.

Tsunehiko Tanaka, Kenshi Abe, Kaito Ariu, Tetsuro Morimura, Edgar Simo-Serra

CoRR, 2024

On Universally Optimal Algorithms for A/B Testing.

Po-An Wang, Kaito Ariu, Alexandre Proutière

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

Matroid Semi-Bandits in Sublinear Time.

Ruo-Chun Tzeng, Naoto Ohsaka, Kaito Ariu

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

Model-Based Minimum Bayes Risk Decoding for Text Generation.

Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe

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

Adaptively Perturbed Mirror Descent for Learning in Games.

Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Atsushi Iwasaki

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

Filtered Direct Preference Optimization.

Tetsuro Morimura, Mitsuki Sakamoto, Yuu Jinnai, Kenshi Abe, Kaito Ariu

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Hyperparameter-Free Approach for Faster Minimum Bayes Risk Decoding.

Yuu Jinnai, Kaito Ariu

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Memory Asymmetry Creates Heteroclinic Orbits to Nash Equilibrium in Learning in Zero-Sum Games.

Yuma Fujimoto, Kaito Ariu, Kenshi Abe

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Model-Based Minimum Bayes Risk Decoding.

Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe

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

Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model.

Kaito Ariu, Alexandre Proutière, Se-Young Yun

CoRR, 2023

A Slingshot Approach to Learning in Monotone Games.

Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Atsushi Iwasaki

CoRR, 2023

Memory Asymmetry: A Key to Convergence in Zero-Sum Games.

Yuma Fujimoto, Kaito Ariu, Kenshi Abe

CoRR, 2023

Exploration of Unranked Items in Safe Online Learning to Re-Rank.

Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Riku Togashi

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from Nash Equilibrium.

Yuma Fujimoto, Kaito Ariu, Kenshi Abe

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games.

Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Kentaro Toyoshima, Atsushi Iwasaki

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

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

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

Thresholded Lasso Bandit.

Kaito Ariu, Kenshi Abe, Alexandre Proutière

Proceedings of the International Conference on Machine Learning, 2022

2021

Optimal Simple Regret in Bayesian Best Arm Identification.

Junpei Komiyama, Kaito Ariu, Masahiro Kato, Chao Qin

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

The Role of Contextual Information in Best Arm Identification.

Masahiro Kato, Kaito Ariu

CoRR, 2021

2020

A Practical Guide of Off-Policy Evaluation for Bandit Problems.

Masahiro Kato, Kenshi Abe, Kaito Ariu, Shota Yasui

CoRR, 2020

Regret in Online Recommendation Systems.

Kaito Ariu, Narae Ryu, Se-Young Yun, Alexandre Proutière

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

Optimal Algorithms for Multiplayer Multi-Armed Bandits.

Po-An Wang, Alexandre Proutière, Kaito Ariu, Yassir Jedra, Alessio Russo

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2017

Chance-Constrained Path Planning with Continuous Time Safety Guarantees.

Kaito Ariu, Cheng Fang, Márcio da Silva Arantes, Cláudio Toledo, Brian Charles Williams

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017