3 citations · 3 across the 1 of their papers we have counts for
3 papers
Interpretable Machine Learning: Moving From Mythos to Diagnostics
Valerie Chen, Jeffrey Li, Joon Sik Kim +2
Despite increasing interest in the field of Interpretable Machine Learning (IML), a significant gap persists between the technical objectives targeted by researchers' methods and t…
A Learning Theoretic Perspective on Local Explainability
Jeffrey Li, Vaishnavh Nagarajan, Gregory Plumb +1
In this paper, we explore connections between interpretable machine learning and learning theory through the lens of local approximation explanations. First, we tackle the traditio…
Differentially Private Meta-Learning
Jeffrey Li, Mikhail Khodak, Sebastian Caldas +1
Parameter-transfer is a well-known and versatile approach for meta-learning, with applications including few-shot learning, federated learning, and reinforcement learning. However,…