Kenshi Abe - RankMe

55 papers A* 12A 7Journal 35Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Linear Convergence in Games with Delayed Feedback via Extra Prediction. CoRR Yuma Fujimoto, Kenshi Abe, Kaito Ariu
2025	A*	`conf`	Approximate State Abstraction for Markov Games. AAAI Hiroki Ishibashi, Kenshi Abe, Atsushi Iwasaki
2025	A*	`conf`	Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games. ICLR Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu, Atsushi Iwasaki
2025	A	`conf`	Efficient Creative Selection in Online Advertising using Top-Two Thompson Sampling. WSDM Daiki Katsuragawa, Yusuke Kaneko, Kaito Ariu, Kenshi Abe
2025	J	`jnl`	Evaluation of Best-of-N Sampling Strategies for Language Model Alignment. CoRR Yuki Ichihara, Yuu Jinnai, Tetsuro Morimura, Kaito Ariu, Kenshi Abe, Mitsuki Sakamoto, Eiji Uchibe
2025	J	`jnl`	Evaluation of Best-of-N Sampling Strategies for Language Model Alignment. Trans. Mach. Learn. Res. Yuki Ichihara, Yuu Jinnai, Tetsuro Morimura, Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Eiji Uchibe
2025	A	`conf`	Global Behavior of Learning Dynamics in Zero-Sum Games with Memory Asymmetry. AAMAS Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2025	J	`jnl`	Learning from Delayed Feedback in Games via Extra Prediction. CoRR Yuma Fujimoto, Kenshi Abe, Kaito Ariu
2025	A	`conf`	Nash Equilibrium and Learning Dynamics in Three-Player Matching AAMAS Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2025	J	`jnl`	Policy Testing in Markov Decision Processes. CoRR Kaito Ariu, Po-An Wang, Alexandre Proutière, Kenshi Abe
2025	—	`conf`	Regularized Best-of-N Sampling with Minimum Bayes Risk Objective for Language Model Alignment. NAACL (Long Papers) Yuu Jinnai, Tetsuro Morimura, Kaito Ariu, Kenshi Abe
2025	J	`jnl`	Return-Aligned Decision Transformer. Trans. Mach. Learn. Res. Tsunehiko Tanaka, Kenshi Abe, Kaito Ariu, Tetsuro Morimura, Edgar Simo-Serra
2025	A*	`conf`	Synchronization in Learning in Periodic Zero-Sum Games Triggers Divergence from Nash Equilibrium. AAAI Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2025	J	`jnl`	The Power of Perturbation under Sampling in Solving Extensive-Form Games. CoRR Wataru Masaka, Mitsuki Sakamoto, Kenshi Abe, Kaito Ariu, Tuomas Sandholm, Atsushi Iwasaki
2024	A*	`conf`	Adaptively Perturbed Mirror Descent for Learning in Games. ICML Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Atsushi Iwasaki
2024	J	`jnl`	Approximate State Abstraction for Markov Games. CoRR Hiroki Ishibashi, Kenshi Abe, Atsushi Iwasaki
2024	J	`jnl`	Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games. CoRR Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu, Atsushi Iwasaki
2024	A*	`conf`	Filtered Direct Preference Optimization. EMNLP Tetsuro Morimura, Mitsuki Sakamoto, Yuu Jinnai, Kenshi Abe, Kaito Ariu
2024	J	`jnl`	Filtered Direct Preference Optimization. CoRR Tetsuro Morimura, Mitsuki Sakamoto, Yuu Jinnai, Kenshi Abe, Kaito Ariu
2024	J	`jnl`	Global Behavior of Learning Dynamics in Zero-Sum Games with Memory Asymmetry. CoRR Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2024	J	`jnl`	Last Iterate Convergence in Monotone Mean Field Games. CoRR Noboru Isobe, Kenshi Abe, Kaito Ariu
2024	A	`conf`	Learning Fair Division from Bandit Feedback. AISTATS Hakuei Yamada, Junpei Komiyama, Kenshi Abe, Atsushi Iwasaki
2024	A*	`conf`	Memory Asymmetry Creates Heteroclinic Orbits to Nash Equilibrium in Learning in Zero-Sum Games. AAAI Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2024	A*	`conf`	Model-Based Minimum Bayes Risk Decoding for Text Generation. ICML Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe
2024	J	`jnl`	Nash Equilibrium and Learning Dynamics in Three-Player Matching m-Action Games. CoRR Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2024	J	`jnl`	Policy Gradient Algorithms with Monte Carlo Tree Learning for Non-Markov Decision Processes. RLJ Tetsuro Morimura, Kazuhiro Ota, Kenshi Abe, Peinan Zhang
2024	J	`jnl`	Regularized Best-of-N Sampling to Mitigate Reward Hacking for Language Model Alignment. CoRR Yuu Jinnai, Tetsuro Morimura, Kaito Ariu, Kenshi Abe
2024	J	`jnl`	Return-Aligned Decision Transformer. CoRR Tsunehiko Tanaka, Kenshi Abe, Kaito Ariu, Tetsuro Morimura, Edgar Simo-Serra
2024	A*	`conf`	Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems. WWW Riku Togashi, Kenshi Abe, Yuta Saito
2024	J	`jnl`	Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems. CoRR Riku Togashi, Kenshi Abe, Yuta Saito
2024	J	`jnl`	Synchronization behind Learning in Periodic Zero-Sum Games Triggers Divergence from Nash equilibrium. CoRR Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2024	J	`jnl`	Time-Varyingness in Auction Breaks Revenue Equivalence. CoRR Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2023	J	`jnl`	A Slingshot Approach to Learning in Monotone Games. CoRR Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Atsushi Iwasaki
2023	A*	`conf`	Exploration of Unranked Items in Safe Online Learning to Re-Rank. SIGIR Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Riku Togashi
2023	J	`jnl`	Exploration of Unranked Items in Safe Online Learning to Re-Rank. CoRR Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Riku Togashi
2023	A	`conf`	Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games. AISTATS Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Kentaro Toyoshima, Atsushi Iwasaki
2023	J	`jnl`	Learning Fair Division from Bandit Feedback. CoRR Hakuei Yamada, Junpei Komiyama, Kenshi Abe, Atsushi Iwasaki
2023	A*	`conf`	Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from Nash Equilibrium. IJCAI Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2023	J	`jnl`	Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from Nash Equilibrium. CoRR Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2023	J	`jnl`	Memory Asymmetry: A Key to Convergence in Zero-Sum Games. CoRR Yuma Fujimoto, Kaito Ariu, Kenshi Abe
2023	J	`jnl`	Model-Based Minimum Bayes Risk Decoding. CoRR Yuu Jinnai, Tetsuro Morimura, Ukyo Honda, Kaito Ariu, Kenshi Abe
2023	J	`jnl`	Why Guided Dialog Policy Learning performs well? Understanding the role of adversarial learning and its alternative. CoRR Sho Shimoyama, Tetsuro Morimura, Kenshi Abe, Toda Takamichi, Yuta Tomomatsu, Masakazu Sugiyama, Asahi Hentona, Yuuki Azuma, Hirotaka Ninomiya
2022	A*	`conf`	Anytime Capacity Expansion in Medical Residency Match by Monte Carlo Tree Search. IJCAI Kenshi Abe, Junpei Komiyama, Atsushi Iwasaki
2022	J	`jnl`	Anytime Capacity Expansion in Medical Residency Match by Monte Carlo Tree Search. CoRR Kenshi Abe, Junpei Komiyama, Atsushi Iwasaki
2022	J	`jnl`	Fair Matrix Factorisation for Large-Scale Recommender Systems. CoRR Riku Togashi, Kenshi Abe
2022	J	`jnl`	Last-Iterate Convergence with Full- and Noisy-Information Feedback in Two-Player Zero-Sum Games. CoRR Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Kentaro Toyoshima, Atsushi Iwasaki
2022	J	`jnl`	Mutation-Driven Follow the Regularized Leader for Last-Iterate Convergence in Zero-Sum Games. CoRR Kenshi Abe, Mitsuki Sakamoto, Atsushi Iwasaki
2022	A	`conf`	Mutation-driven follow the regularized leader for last-iterate convergence in zero-sum games. UAI Kenshi Abe, Mitsuki Sakamoto, Atsushi Iwasaki
2022	J	`jnl`	Policy Gradient Algorithms with Monte-Carlo Tree Search for Non-Markov Decision Processes. CoRR Tetsuro Morimura, Kazuhiro Ota, Kenshi Abe, Peinan Zhang
2022	A*	`conf`	Thresholded Lasso Bandit. ICML Kaito Ariu, Kenshi Abe, Alexandre Proutière
2021	A	`conf`	Off-Policy Exploitability-Evaluation in Two-Player Zero-Sum Markov Games. AAMAS Kenshi Abe, Yusuke Kaneko
2020	J	`jnl`	A Practical Guide of Off-Policy Evaluation for Bandit Problems. CoRR Masahiro Kato, Kenshi Abe, Kaito Ariu, Shota Yasui
2020	J	`jnl`	Off-Policy Exploitability-Evaluation and Equilibrium-Learning in Two-Player Zero-Sum Markov Games. CoRR Kenshi Abe, Yusuke Kaneko
2020	J	`jnl`	Thresholded LASSO Bandit. CoRR Kaito Ariu, Kenshi Abe, Alexandre Proutière
2019	J	`jnl`	A Simple Heuristic for Bayesian Optimization with A Low Budget. CoRR Masahiro Nomura, Kenshi Abe