1 citations · 1 across the 2 of their papers we have counts for
5 papers
Additive Logistic Mechanism for Privacy-Preserving Self-Supervised Learning
Yunhao Yang, Parham Gohari, Ufuk Topcu
We study the privacy risks that are associated with training a neural network's weights with self-supervised learning algorithms. Through empirical evidence, we show that the fine-…
Privacy-Preserving Kickstarting Deep Reinforcement Learning with Privacy-Aware Learners
Parham Gohari, Bo Chen, Bo Wu +2
Kickstarting deep reinforcement learning algorithms facilitate a teacher-student relationship among the agents and allow for a well-performing teacher to share demonstrations with…
Blending Controllers via Multi-Objective Bandits
Parham Gohari, Franck Djeumou, Abraham P. Vinod +1
Safety and performance are often two competing objectives in sequential decision-making problems. Existing performant controllers, such as controllers derived from reinforcement le…
Privacy-Preserving Policy Synthesis in Markov Decision Processes
Parham Gohari, Matthew Hale, Ufuk Topcu
In decision-making problems, the actions of an agent may reveal sensitive information that drives its decisions. For instance, a corporation's investment decisions may reveal its s…
The Dirichlet Mechanism for Differential Privacy on the Unit Simplex
Parham Gohari, Bo Wu, Matthew Hale +1
As members of a network share more information with each other and network providers, sensitive data leakage raises privacy concerns. To address this need for a class of problems,…