Current Projects

  1. Dokyun Lee, Eric Zhou, Chengfeng Mao, Gerald Kane. Interpretable Machine Learning Can Be Useful Tools For Theory Building: A Human-AI Collaboration.
    Accepted to MISQ Author Workshop 2020. Work in progress.

    “Recent advances in Interpretable Machine Learning (IML) offer potential flexible, scalable solutions to augment novel hypothesis development, especially with exponential growth in unstructured data. We demonstrate by applying a novel IML algorithm on three datasets to reproduce theory-driven insights from literature.”

  2. Focused Concept Miner User Guide for alpha/beta release. See the original paper, Focused Concept Miner (FCM): Interpretable Deep Learning for Text Exploration and for details.