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Achievement: YOLOAchievement: Pull Sharkx3Achievement: Pair Extraordinairex3Achievement: QuickdrawAchievement: StarstruckAchievement: Arctic Code Vault Contributor

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nabenabe0928/README.md

Hi there 👋 I'm Shuhei Watanabe

I am a Research Engineer at Preferred Networks Inc. Prior to the company, I was studying at the University of Freiburg under the supervision of Prof. Frank Hutter. My specialization lies in Hyperparameter optimization and the interpretation of its results.

Website - GH Pages

Shuhei's GitHub stats

🎓 Recent Publications

➡️ All publications...

📫 Email: [email protected]

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  1. tpe tpe Public

    The tree-structured Parzen estimator (TPE) implementation and the simple running code for it

    Python 60 4

  2. constrained-tpe constrained-tpe Public

    [IJCAI'23] c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization

    Jupyter Notebook 8 2

  3. local-anova local-anova Public

    [IJCAI'23] PED-ANOVA: Efficiently Quantifying Hyperparameter Importance in Arbitrary Subspaces

    Python 7

  4. meta-learn-tpe meta-learn-tpe Public

    [IJCAI'23] Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator

    Jupyter Notebook 9 3

  5. mfhpo-simulator mfhpo-simulator Public

    [Python3] The simulator for multi-fidelity or parallel optimization using tabular or surrogate benchmarks

    Python 7

  6. empirical-attainment-func empirical-attainment-func Public

    [Python3] The visualization for multi-objective optimization based on empirical attainment function.

    Python 4 1