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@ishida-lab

Machine Evaluation and Learning @ UTokyo

We are a sub-group of Machine Learning and Statistical Data Analysis Lab (mslab) in UTokyo, with a focus on machine evaluation and learning (MEAL).

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  1. irreducible irreducible Public

    [ICLR 2023] Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification

    Python 21

  2. IW-DPO IW-DPO Public

    [TMLR 2025] Importance Weighting for Aligning Language Models under Deployment Distribution Shift

    Python 5

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Showing 2 of 2 repositories
  • irreducible Public

    [ICLR 2023] Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification

    ishida-lab/irreducible’s past year of commit activity
    Python 21 GPL-3.0 0 0 0 Updated Aug 12, 2025
  • IW-DPO Public

    [TMLR 2025] Importance Weighting for Aligning Language Models under Deployment Distribution Shift

    ishida-lab/IW-DPO’s past year of commit activity
    Python 5 Apache-2.0 0 0 0 Updated Jul 22, 2025

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