2 papers
math.OC2025
On the Inherent Privacy of Zeroth Order Projected Gradient Descent
Devansh Gupta, Meisam Razaviyayn, Vatsal Sharan
Differentially private zeroth-order optimization methods have recently gained popularity in private fine tuning of machine learning models due to their reduced memory requirements.…
cs.LG2024
A Stochastic Optimization Framework for Private and Fair Learning From Decentralized Data
Devansh Gupta, A. S. Poornash, Andrew Lowy +1
Machine learning models are often trained on sensitive data (e.g., medical records and race/gender) that is distributed across different "silos" (e.g., hospitals). These federated…