1 citations · 2 across the 8 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.LG2024★ 1 cited
Certification for Differentially Private Prediction in Gradient-Based Training
Matthew Wicker, Philip Sosnin, Igor Shilov +5
We study private prediction where differential privacy is achieved by adding noise to the outputs of a non-private model. Existing methods rely on noise proportional to the global…
cs.LG2024
Certified Robustness to Data Poisoning in Gradient-Based Training
Philip Sosnin, Mark N. Müller, Maximilian Baader +2
Modern machine learning pipelines leverage large amounts of public data, making it infeasible to guarantee data quality and leaving models open to poisoning and backdoor attacks. P…
math.OC2024★ 1 cited
Scaling Mixed-Integer Programming for Certification of Neural Network Controllers Using Bounds Tightening
Philip Sosnin, Calvin Tsay
Neural networks offer a computationally efficient approximation of model predictive control, but they lack guarantees on the resulting controlled system's properties. Formal certif…