Yuta Saito

Yuta Saito

Second-year CS Ph.D. Student

Cornell University

Biography

I’m a second-year Ph.D. student in Computer Science at Cornell University, where I’m fortunate to be advised by Prof. Thorsten Joachims. I completed my bachelor’s degree in Industrial Engineering and Economics at the Tokyo Institute of Technology.

My research lies at the intersection of machine learning and causal inference called counterfactual learning. I am interested in the counterfactual nature of logged bandit feedback and human behavior data obtained from interactive systems, and ways of using biased real-world datasets to assist safe and better decision making in the wild.

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Interests
  • Counterfactual Evaluation
  • Learning from Behavior Data
  • Statistical Machine Learning
  • Fairness in Ranking
Education
  • PhD in Computer Science, 2021 -

    Cornell University

  • B.Eng in Industrial Engineering, 2016 - 2021

    Tokyo Institute of Technology

Recent & Upcoming Talks

Counterfactual Tutorial at KDD2022
KDD2022 Tutorial on Counterfactual Evaluation and Learning
Counterfactual Tutorial at RecSys2021
RecSys2021 Tutorial on Counterfactual Evaluation and Learning

Recent Publications

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(2022). Policy-Adaptive Estimator Selection for Off-Policy Evaluation. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI) (Acceptance rate=19.6%).

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(2022). Counterfactual Evaluation and Learning for Interactive Systems. In Proceedings of the 28th SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).

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(2022). Towards Resolving Propensity Contradiction in Offline Recommender Learning. In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI) (Acceptance rate=15%, Long Talk (top 4% of submissions)).

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(2022). Unbiased Recommender Learning from Biased Graded Implicit Feedback. WSDM 2022 Workshop on Decision Making for Modern Information Retrieval System.

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(2021). A Real-World Implementation of Unbiased Lift-based Bidding System. In Proceedings of the 2021 IEEE International Conference on Big Data (IEEE Big Data).

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Awards

Paper Awards

Outstanding Reviewer Awards

Other Awards

Scholarships

Relevant Courses

Fall 2023

  • CS6410: Advanced Systems
  • CS6784: Machine Learning in Feedback Systems

Spring 2022

  • ORIE6170: Engineering Societal Systems

Fall 2021

  • CS6787: Advanced Machine Learning Systems
  • CS7792: Fairness and Dynamics of Learning Systems

Academic Service

Conference Program Committee

Workshop Organizer

Workshop Program Committee

Journal Reviewer

  • ACM Transactions on Intelligent Systems and Technology (TIST)
  • ACM Transactions on Information Systems (TOIS)
  • ACM Transactions on Recommender Systems (TORS)
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • Transactions on Machine Learning Research (TMLR)

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