38 citations · 38 across the 1 of their papers we have counts for
3 papers
cs.LG2022★ 38 cited
Data Privacy and Trustworthy Machine Learning
Martin Strobel, Reza Shokri
The privacy risks of machine learning models is a major concern when training them on sensitive and personal data. We discuss the tradeoffs between data privacy and the remaining g…
cs.LG2020
High Dimensional Model Explanations: an Axiomatic Approach
Neel Patel, Martin Strobel, Yair Zick
Complex black-box machine learning models are regularly used in critical decision-making domains. This has given rise to several calls for algorithmic explainability. Many explanat…
cs.LG2019
On the Privacy Risks of Model Explanations
Reza Shokri, Martin Strobel, Yair Zick
Privacy and transparency are two key foundations of trustworthy machine learning. Model explanations offer insights into a model's decisions on input data, whereas privacy is prima…