Yusuke Narita

According to our database, Yusuke Narita authored at least 16 papers between 2014 and 2023.

Collaborative distances:

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

2023

Off-Policy Evaluation of Ranking Policies under Diverse User Behavior.

Haruka Kiyohara, Masatoshi Uehara, Yusuke Narita, Nobuyuki Shimizu, Yasuo Yamamoto, Yuta Saito

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Policy-Adaptive Estimator Selection for Off-Policy Evaluation.

Takuma Udagawa, Haruka Kiyohara, Yusuke Narita, Yuta Saito, Kei Tateno

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Counterfactual Learning with General Data-Generating Policies.

Yusuke Narita, Kyohei Okumura, Akihiro Shimizu, Kohei Yata

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

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

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

2021

A Theory of Quasi-Experimental Evaluation of School Quality.

Yusuke Narita

Manag. Sci., 2021

Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules.

Yusuke Narita, Kohei Yata

CoRR, 2021

Evaluating the Robustness of Off-Policy Evaluation.

Yuta Saito, Takuma Udagawa, Haruka Kiyohara, Kazuki Mogi, Yusuke Narita, Kei Tateno

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Debiased Off-Policy Evaluation for Recommendation Systems.

Yusuke Narita, Shota Yasui, Kohei Yata

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation.

Yuta Saito, Shunsuke Aihara, Megumi Matsutani, Yusuke Narita

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

A Large-scale Open Dataset for Bandit Algorithms.

Yuta Saito, Shunsuke Aihara, Megumi Matsutani, Yusuke Narita

CoRR, 2020

Safe Counterfactual Reinforcement Learning.

Yusuke Narita, Shota Yasui, Kohei Yata

CoRR, 2020

Adaptive Experimental Design for Efficient Treatment Effect Estimation: Randomized Allocation via Contextual Bandit Algorithm.

Masahiro Kato, Takuya Ishihara, Junya Honda, Yusuke Narita

CoRR, 2020

2019

Efficient Counterfactual Learning from Bandit Feedback.

Yusuke Narita, Shota Yasui, Kohei Yata

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2016

Improving schools through school choice: A market design approach.

John William Hatfield, Fuhito Kojima, Yusuke Narita

J. Econ. Theory, 2016

Interactive Object Extraction from a Video Based on Seed-Line Tracking.

Takahiro Hayashi, Yusuke Narita

Proceedings of the International Conference on Multimedia Systems and Signal Processing, 2016

2014

Many-to-many matching with max-min preferences.

John William Hatfield, Fuhito Kojima, Yusuke Narita

Discret. Appl. Math., 2014