Distributed Optimization for Client-Server Architecture with Negative Gradient Weights. - Shripad Gade; Nitin H. Vaidya (CoRR, 2016)

Distributed Optimization of Convex Sum of Non-Convex Functions. - Shripad Gade; Nitin H. Vaidya (CoRR, 2016)

Private Learning on Networks. - Shripad Gade; Nitin H. Vaidya (CoRR, 2016)

Private Learning on Networks: Part II. - Shripad Gade; Nitin H. Vaidya (CoRR, 2017)

Private Optimization on Networks. - Shripad Gade; Nitin H. Vaidya (ACC, 2018)

Privacy-Preserving Distributed Learning via Obfuscated Stochastic Gradients. - Shripad Gade; Nitin H. Vaidya (CDC, 2018)

On Privatizing Equilibrium Computation in Aggregate Games over Networks. - Shripad Gade; Anna Winnicki; Subhonmesh Bose (CoRR, 2019)

Toward Resilient Multi-Agent Actor-Critic Algorithms for Distributed Reinforcement Learning. - Yixuan Lin; Shripad Gade; Romeil Sandhu; Ji Liu 001 (ACC, 2020)

A Private and Finite-Time Algorithm for Solving a Distributed System of Linear Equations. - Shripad Gade; Ji Liu 001; Nitin H. Vaidya (CoRR, 2020)

Accuracy-aware privacy mechanisms for distributed computation - Shripad Gade (2020)

Preserving Statistical Privacy in Distributed Optimization. - Nirupam Gupta; Shripad Gade; Nikhil Chopra; Nitin H. Vaidya (IEEE Control. Syst. Lett., 2021)

Leveraging Vertical Public-Private Split for Improved Synthetic Data Generation. - Samuel Maddock; Shripad Gade; Graham Cormode; Will Bullock (CoRR, 2025)

Synthetic Tabular Data: Methods, Attacks and Defenses. - Graham Cormode; Samuel Maddock; Enayat Ullah; Shripad Gade (CoRR, 2025)