Jinsung Yoon

RL-LIM: Reinforcement Learning-based Locally Interpretable Modeling

2019 · arXiv (Cornell University)

Understanding black-box machine learning models is important towards their widespread adoption. However, developing globally interpretable models that explain the behavior of the entire model is challenging. An alternative approach is to explain black-box models through …

Data-Efficient and Interpretable Tabular Anomaly Detection

2022 · arXiv (Cornell University)

Anomaly detection (AD) plays an important role in numerous applications. We focus on two understudied aspects of AD that are critical for integration into real-world applications. First, most AD methods cannot incorporate labeled data that …