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Publications
Publications
  • 2020
  • Conference Presentation

An Empirical Study of the Trade-Offs Between Interpretability and Fairness

By: Shahin Jabbari, Han-Ching Ou, Himabindu Lakkaraju and Milind Tambe
  • Format:Print
  • | Language:English
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Citation

Jabbari, Shahin, Han-Ching Ou, Himabindu Lakkaraju, and Milind Tambe. "An Empirical Study of the Trade-Offs Between Interpretability and Fairness." Paper presented at the ICML Workshop on Human Interpretability in Machine Learning, International Conference on Machine Learning (ICML), 2020.
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About The Author

Himabindu Lakkaraju

Technology and Operations Management
→More Publications

More from the Authors

    • 2023
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    When Algorithms Explain Themselves: AI Adoption and Accuracy of Experts' Decisions

    By: Himabindu Lakkaraju and Chiara Farronato
    • 2022
    • Advances in Neural Information Processing Systems (NeurIPS)

    Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations

    By: Tessa Han, Suraj Srinivas and Himabindu Lakkaraju
    • 2022
    • Advances in Neural Information Processing Systems (NeurIPS)

    Efficiently Training Low-Curvature Neural Networks

    By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
More from the Authors
  • When Algorithms Explain Themselves: AI Adoption and Accuracy of Experts' Decisions By: Himabindu Lakkaraju and Chiara Farronato
  • Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations By: Tessa Han, Suraj Srinivas and Himabindu Lakkaraju
  • Efficiently Training Low-Curvature Neural Networks By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
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