17 citations · 23 across the 5 of their papers we have counts for
6 papers
Auditing Apple's DifferentialPrivacy.framework: Implementation Bugs, Misconfigurations, and Practical Risks
Rishav Chourasia, Ergute Bao, Uzair Javaid +1
Since 2016, Apple has claimed that device analytics collected to improve user experience are protected by differential privacy (DP). Apple's DifferentialPrivacy framework is deploy…
Laplace Transform Interpretation of Differential Privacy
Rishav Chourasia, Uzair Javaid, Biplap Sikdar
We introduce a set of useful expressions of Differential Privacy (DP) notions in terms of the Laplace transform of the privacy loss distribution. Its bare form expression appears i…
Forget Unlearning: Towards True Data-Deletion in Machine Learning
Rishav Chourasia, Neil Shah
Unlearning algorithms aim to remove deleted data's influence from trained models at a cost lower than full retraining. However, prior guarantees of unlearning in literature are fla…
Knowledge Cross-Distillation for Membership Privacy
Rishav Chourasia, Batnyam Enkhtaivan, Kunihiro Ito +3
A membership inference attack (MIA) poses privacy risks for the training data of a machine learning model. With an MIA, an attacker guesses if the target data are a member of the t…
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent
Rishav Chourasia, Jiayuan Ye, Reza Shokri
What is the information leakage of an iterative randomized learning algorithm about its training data, when the internal state of the algorithm is \emph{private}? How much is the c…
Unifying Ensemble Methods for Q-learning via Social Choice Theory
Rishav Chourasia, Adish Singla
Ensemble methods have been widely applied in Reinforcement Learning (RL) in order to enhance stability, increase convergence speed, and improve exploration. These methods typically…