1.6k citations · 2.6k across the 33 of their papers we have counts for
7 papers · 1 filter
On the Privacy Risks of Algorithmic Fairness
Hongyan Chang, Reza Shokri
Algorithmic fairness and privacy are essential pillars of trustworthy machine learning. Fair machine learning aims at minimizing discrimination against protected groups by, for exa…
SOTERIA: In Search of Efficient Neural Networks for Private Inference
Anshul Aggarwal, Trevor E. Carlson, Reza Shokri +1
ML-as-a-service is gaining popularity where a cloud server hosts a trained model and offers prediction (inference) service to users. In this setting, our objective is to protect th…
Improving Deep Learning with Differential Privacy using Gradient Encoding and Denoising
Milad Nasr, Reza Shokri, Amir houmansadr
Deep learning models leak significant amounts of information about their training datasets. Previous work has investigated training models with differential privacy (DP) guarantees…
ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning
Sasi Kumar Murakonda, Reza Shokri
When building machine learning models using sensitive data, organizations should ensure that the data processed in such systems is adequately protected. For projects involving mach…
Model Explanations with Differential Privacy
Neel Patel, Reza Shokri, Yair Zick
Black-box machine learning models are used in critical decision-making domains, giving rise to several calls for more algorithmic transparency. The drawback is that model explanati…
On Adversarial Bias and the Robustness of Fair Machine Learning
Hongyan Chang, Ta Duy Nguyen, Sasi Kumar Murakonda +2
Optimizing prediction accuracy can come at the expense of fairness. Towards minimizing discrimination against a group, fair machine learning algorithms strive to equalize the behav…
Epione: Lightweight Contact Tracing with Strong Privacy
Ni Trieu, Kareem Shehata, Prateek Saxena +2
Contact tracing is an essential tool in containing infectious diseases such as COVID-19. Many countries and research groups have launched or announced mobile apps to facilitate con…