12 citations · 41 across the 8 of their papers we have counts for
12 papers
Exact Unlearning via Quantized Sufficient Statistics
Ami Tavory, Shripad Gade, Tal Sarig +2
Exact unlearning requires a deployed predictor to match one rebuilt without the information named by a deletion request. Existing general-purpose exact methods localize retraining…
Canaries in the Bank: Auditing User-Level Privacy in Private Evolution
Sai Aparna Aketi, Enayat Ullah, Shripad Gade
Private Evolution (PE) generates high-fidelity synthetic data in federated settings without exposing users' raw data. It aggregates clipped user votes over a shared candidate bank…
GEM+: Scalable State-of-the-Art Private Synthetic Data with Generator Networks
Samuel Maddock, Shripad Gade, Graham Cormode +1
State-of-the-art differentially private synthetic tabular data has been defined by adaptive 'select-measure-generate' frameworks, exemplified by methods like AIM. These approaches…
Synthetic Tabular Data: Methods, Attacks and Defenses
Graham Cormode, Samuel Maddock, Enayat Ullah +1
Synthetic data is often positioned as a solution to replace sensitive fixed-size datasets with a source of unlimited matching data, freed from privacy concerns. There has been much…
Leveraging Vertical Public-Private Split for Improved Synthetic Data Generation
Samuel Maddock, Shripad Gade, Graham Cormode +1
Differentially Private Synthetic Data Generation (DP-SDG) is a key enabler of private and secure tabular-data sharing, producing artificial data that carries through the underlying…
A Private and Finite-Time Algorithm for Solving a Distributed System of Linear Equations
Shripad Gade, Ji Liu, Nitin H. Vaidya
This paper studies a system of linear equations, denoted as , which is horizontally partitioned (rows in and ) and stored over a network of devices connected in…