Publications

Refereed Conference Papers

  1. Yuta Saito.
    Doubly Robust Estimator for Ranking Metrics with Post-Click Conversions.
    ACM Conference on Recommender Systems (RecSys2020). (Acceptance rate=17.9%)
    [preprint] [code]

  2. Yuta Saito.
    Unbiased Pairwise Learning from Biased Implicit Feedback.
    International Conference on the Theory of Information Retrieval (ICTIR2020). (Acceptance rate=40.5%)
    [preprint] [code]

  3. Yuta Saito and Shota Yasui.
    Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models.
    International Conference on Machine Learning (ICML2020). (Acceptance rate=21.8%)
    [preprint] [code] [slides]

  4. Yuta Saito.
    Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback.
    International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2020). (Acceptance rate=26.5%)
    [preprint] [code] [slides]

  5. Yuta Saito, Gota Morishita, and Shota Yasui.
    Dual Learning Algorithm for Delayed Conversions.
    International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2020). (Acceptance rate of short paper=30.2%)
    [paper] [slides]

  6. Yuta Saito, Hayato Sakata, and Kazuhide Nakata.
    Cost-Effective and Stable Policy Optimization Algorithm for Uplift Modeling with Multiple Treatments.
    SIAM International Conference on Data Mining (SDM2020). (Acceptance rate=24.0%)
    [paper] [supplementary material]

  7. Yuta Saito, Suguru Yaginuma, Yuta Nishino, Hayato Sakata, and Kazuhide Nakata.
    Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback.
    International Conference on Web Search and Data Mining (WSDM2020). (Acceptance rate=14.8%)
    [paper] [code] [slides]

  8. Yuta Saito, Hayato Sakata, and Kazuhide Nakata.
    Doubly Robust Prediction and Evaluation Methods Improve Uplift Modeling for Observational Data.
    SIAM International Conference on Data Mining (SDM2019). (Acceptance rate=22.7%)
    [paper] [supplementary material]

Refereed Workshop Papers

  1. Daisuke Moriwaki, Yuta Hayakawa, Isshu Munemasa, Yuta Saito, and Akira Matsui.
    Unbiased Lift-based Bidding System.
    AdKDD & TargetAd 2020 Workshop (held in conjunction with KDD2020) (AdKDD2020).
    [arXiv]

  2. Masahiro Nomura and Yuta Saito (equal contribution).
    Multi-Source Unsupervised Hyperparameter Optimization.
    ICML 2020 Workshop on Automated Machine Learning (AutoML2020). (Acceptance rate=58.7%)
    [arXiv] [code]

  3. Yuta Saito.
    Offline Recommender Learning Meets Unsupervised Domain Adaptation.
    The forum for newcomers to ML (held in conjunction with NeurIPS2019) (NewInML2019).
    [arXiv]