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ORCIDKaito Ariu
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2020 – today
- 2024
[j2]Kaito Ariu
, Jungseul Ok, Alexandre Proutière, Seyoung Yun:
Optimal clustering from noisy binary feedback. Mach. Learn. 113(5): 2733-2764 (2024)- [j1]Junpei Komiyama, Kaito Ariu, Masahiro Kato, Chao Qin:
Rate-Optimal Bayesian Simple Regret in Best Arm Identification. Math. Oper. Res. 49(3): 1629-1646 (2024) - [c14]Yuma Fujimoto, Kaito Ariu, Kenshi Abe:
Memory Asymmetry Creates Heteroclinic Orbits to Nash Equilibrium in Learning in Zero-Sum Games. AAAI 2024: 17398-17406 - [c13]Yuu Jinnai, Kaito Ariu:
Hyperparameter-Free Approach for Faster Minimum Bayes Risk Decoding. ACL (Findings) 2024: 8547-8566 - [c12]Tetsuro Morimura, Mitsuki Sakamoto, Yuu Jinnai, Kenshi Abe, Kaito Ariu:
Filtered Direct Preference Optimization. EMNLP 2024: 22729-22770 - [c11]Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Atsushi Iwasaki:
Adaptively Perturbed Mirror Descent for Learning in Games. ICML 2024 - [c10]Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe:
Model-Based Minimum Bayes Risk Decoding for Text Generation. ICML 2024 - [c9]Ruo-Chun Tzeng, Naoto Ohsaka, Kaito Ariu:
Matroid Semi-Bandits in Sublinear Time. ICML 2024 - [c8]Po-An Wang, Kaito Ariu, Alexandre Proutière:
On Universally Optimal Algorithms for A/B Testing. ICML 2024 - [i27]Yuu Jinnai, Kaito Ariu:
Hyperparameter-Free Approach for Faster Minimum Bayes Risk Decoding. CoRR abs/2401.02749 (2024) - [i26]Tsunehiko Tanaka, Kenshi Abe, Kaito Ariu, Tetsuro Morimura, Edgar Simo-Serra:
Return-Aligned Decision Transformer. CoRR abs/2402.03923 (2024) - [i25]Yuma Fujimoto, Kaito Ariu, Kenshi Abe:
Nash Equilibrium and Learning Dynamics in Three-Player Matching m-Action Games. CoRR abs/2402.10825 (2024) - [i24]Yuu Jinnai, Tetsuro Morimura, Kaito Ariu, Kenshi Abe:
Regularized Best-of-N Sampling to Mitigate Reward Hacking for Language Model Alignment. CoRR abs/2404.01054 (2024) - [i23]Tetsuro Morimura, Mitsuki Sakamoto, Yuu Jinnai, Kenshi Abe, Kaito Ariu:
Filtered Direct Preference Optimization. CoRR abs/2404.13846 (2024) - [i22]Yuma Fujimoto, Kaito Ariu, Kenshi Abe:
Global Behavior of Learning Dynamics in Zero-Sum Games with Memory Asymmetry. CoRR abs/2405.14546 (2024) - [i21]Ruo-Chun Tzeng, Naoto Ohsaka, Kaito Ariu:
Matroid Semi-Bandits in Sublinear Time. CoRR abs/2405.17968 (2024) - [i20]Yuma Fujimoto, Kaito Ariu, Kenshi Abe:
Synchronization behind Learning in Periodic Zero-Sum Games Triggers Divergence from Nash equilibrium. CoRR abs/2408.10595 (2024) - [i19]Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu, Atsushi Iwasaki:
Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games. CoRR abs/2410.02388 (2024) - [i18]Noboru Isobe, Kenshi Abe, Kaito Ariu:
Last Iterate Convergence in Monotone Mean Field Games. CoRR abs/2410.05127 (2024) - [i17]Yuma Fujimoto, Kaito Ariu, Kenshi Abe:
Time-Varyingness in Auction Breaks Revenue Equivalence. CoRR abs/2410.12306 (2024) - 2023
- [c7]Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Kentaro Toyoshima, Atsushi Iwasaki:
Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games. AISTATS 2023: 7999-8028 - [c6]Yuma Fujimoto, Kaito Ariu, Kenshi Abe:
Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from Nash Equilibrium. IJCAI 2023: 118-125 - [c5]Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Riku Togashi:
Exploration of Unranked Items in Safe Online Learning to Re-Rank. SIGIR 2023: 1991-1995 - [i16]Yuma Fujimoto, Kaito Ariu, Kenshi Abe:
Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from Nash Equilibrium. CoRR abs/2302.01073 (2023) - [i15]Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Riku Togashi:
Exploration of Unranked Items in Safe Online Learning to Re-Rank. CoRR abs/2305.01202 (2023) - [i14]Yuma Fujimoto, Kaito Ariu, Kenshi Abe:
Memory Asymmetry: A Key to Convergence in Zero-Sum Games. CoRR abs/2305.13619 (2023) - [i13]Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Atsushi Iwasaki:
A Slingshot Approach to Learning in Monotone Games. CoRR abs/2305.16610 (2023) - [i12]Kaito Ariu, Alexandre Proutière, Se-Young Yun:
Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model. CoRR abs/2306.12968 (2023) - [i11]Po-An Wang, Kaito Ariu, Alexandre Proutière:
On Uniformly Optimal Algorithms for Best Arm Identification in Two-Armed Bandits with Fixed Budget. CoRR abs/2308.12000 (2023) - [i10]Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe:
Model-Based Minimum Bayes Risk Decoding. CoRR abs/2311.05263 (2023) - 2022
- [c4]Kaito Ariu, Kenshi Abe, Alexandre Proutière:
Thresholded Lasso Bandit. ICML 2022: 878-928 - [i9]Masahiro Kato, Kaito Ariu, Masaaki Imaizumi, Masatoshi Uehara, Masahiro Nomura, Chao Qin:
Optimal Fixed-Budget Best Arm Identification using the Augmented Inverse Probability Weighting Estimator in Two-Armed Gaussian Bandits with Unknown Variances. CoRR abs/2201.04469 (2022) - [i8]Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Kentaro Toyoshima, Atsushi Iwasaki:
Last-Iterate Convergence with Full- and Noisy-Information Feedback in Two-Player Zero-Sum Games. CoRR abs/2208.09855 (2022) - 2021
- [i7]Masahiro Kato, Kaito Ariu:
The Role of Contextual Information in Best Arm Identification. CoRR abs/2106.14077 (2021) - [i6]Kaito Ariu, Masahiro Kato, Junpei Komiyama, Kenichiro McAlinn:
Policy Choice and Best Arm Identification: Comments on "Adaptive Treatment Assignment in Experiments for Policy Choice". CoRR abs/2109.08229 (2021) - [i5]Junpei Komiyama, Kaito Ariu, Masahiro Kato, Chao Qin:
Optimal Simple Regret in Bayesian Best Arm Identification. CoRR abs/2111.09885 (2021) - 2020
- [c3]Po-An Wang, Alexandre Proutière, Kaito Ariu, Yassir Jedra, Alessio Russo:
Optimal Algorithms for Multiplayer Multi-Armed Bandits. AISTATS 2020: 4120-4129 - [c2]Kaito Ariu, Narae Ryu, Se-Young Yun, Alexandre Proutière:
Regret in Online Recommendation Systems. NeurIPS 2020 - [i4]Kaito Ariu, Kenshi Abe, Alexandre Proutière:
Thresholded LASSO Bandit. CoRR abs/2010.11994 (2020) - [i3]Kaito Ariu, Narae Ryu, Se-Young Yun, Alexandre Proutière:
Regret in Online Recommendation Systems. CoRR abs/2010.12363 (2020) - [i2]Masahiro Kato, Kenshi Abe, Kaito Ariu, Shota Yasui:
A Practical Guide of Off-Policy Evaluation for Bandit Problems. CoRR abs/2010.12470 (2020)
2010 – 2019
- 2019
- [i1]Kaito Ariu, Jungseul Ok, Alexandre Proutière, Se-Young Yun:
Optimal Clustering from Noisy Binary Feedback. CoRR abs/1910.06002 (2019) - 2017
- [c1]Kaito Ariu, Cheng Fang, Márcio da Silva Arantes, Cláudio Toledo, Brian Charles Williams:
Chance-Constrained Path Planning with Continuous Time Safety Guarantees. AAAI Workshops 2017
Coauthor Index
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