Microsoft Research Summit: Surprising (and unsurprising) Inference Risks in Machine Learning

Here are the slides for my talk at the Practical and Theoretical Privacy of Machine Learning Training Pipelines Workshop at the Microsoft Research Summit (21 October 2021):

Surprising (and Unsurprising) Inference Risks in Machine Learning [PDF]

The work by Bargav Jayaraman (with Katherine Knipmeyer, Lingxiao Wang, and Quanquan Gu) that I talked about on improving membership inference attacks is described in more details here:

The work on distribution inference is described in this paper (by Anshuman Suri):

The work on attribute inference and imputation isn’t yet posted, but feel free to contact me with any questions about it.