deep learning Probing Deep Network Behavior with Internal Influence In recent work with my colleagues at CMU, we focus on bringing greater transparency to these mysterious, yet effective, machine learning techniques.
machine learning Featured Proxy-Based Approach to Fair Machine Learning We explain the motivation behind our 2018 NeurIPS paper, "Hunting for Discriminatory Proxies in Linear Regression Models".
deep learning Featured Explainability in Neural Networks, Part 2: Limitations of Simple Feature Attribution Methods We examine some simple, intuitive methods to explain the output of a neural network (based on perturbations and gradients), and see how they produce non-sensical results for non-linear functions.
