Many-to-many matching with max-min preferences. - John William Hatfield; Fuhito Kojima; Yusuke Narita (Discret. Appl. Math., 2014)

Interactive Object Extraction from a Video Based on Seed-Line Tracking. - Takahiro Hayashi; Yusuke Narita (ICMSSP, 2016)

Improving schools through school choice: A market design approach. - John William Hatfield; Fuhito Kojima; Yusuke Narita (J. Econ. Theory, 2016)

Efficient Counterfactual Learning from Bandit Feedback. - Yusuke Narita; Shota Yasui; Kohei Yata (AAAI, 2019)

Adaptive Experimental Design for Efficient Treatment Effect Estimation: Randomized Allocation via Contextual Bandit Algorithm. - Masahiro Kato; Takuya Ishihara; Junya Honda; Yusuke Narita (CoRR, 2020)

Safe Counterfactual Reinforcement Learning. - Yusuke Narita; Shota Yasui; Kohei Yata (CoRR, 2020)

A Large-scale Open Dataset for Bandit Algorithms. - Yuta Saito; Shunsuke Aihara; Megumi Matsutani; Yusuke Narita (CoRR, 2020)

Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation. - Yuta Saito; Shunsuke Aihara; Megumi Matsutani; Yusuke Narita (NeurIPS Datasets and Benchmarks, 2021)

Debiased Off-Policy Evaluation for Recommendation Systems. - Yusuke Narita; Shota Yasui; Kohei Yata (RecSys, 2021)

Evaluating the Robustness of Off-Policy Evaluation. - Yuta Saito; Takuma Udagawa; Haruka Kiyohara; Kazuki Mogi; Yusuke Narita; Kei Tateno (RecSys, 2021)

Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules. - Yusuke Narita; Kohei Yata (CoRR, 2021)

A Theory of Quasi-Experimental Evaluation of School Quality. - Yusuke Narita (Manag. Sci., 2021)

Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model. - Haruka Kiyohara; Yuta Saito; Tatsuya Matsuhiro; Yusuke Narita; Nobuyuki Shimizu; Yasuo Yamamoto (WSDM, 2022)

Counterfactual Learning with General Data-Generating Policies. - Yusuke Narita; Kyohei Okumura; Akihiro Shimizu; Kohei Yata (AAAI, 2023)

Policy-Adaptive Estimator Selection for Off-Policy Evaluation. - Takuma Udagawa; Haruka Kiyohara; Yusuke Narita; Yuta Saito; Kei Tateno (AAAI, 2023)

Off-Policy Evaluation of Ranking Policies under Diverse User Behavior. - Haruka Kiyohara; Masatoshi Uehara; Yusuke Narita; Nobuyuki Shimizu; Yasuo Yamamoto; Yuta Saito (KDD, 2023)

Off-Policy Evaluation and Learning for the Future under Non-Stationarity. - Tatsuhiro Shimizu; Kazuki Kawamura; Takanori Muroi; Yusuke Narita; Kei Tateno; Takuma Udagawa; Yuta Saito (KDD (1), 2025)