5 papers · 1 filter
When Do Differentially Private Inputs Protect Graph Shift Operators?
Andrew Campbell, Chenyue Zhang, Hang Liu +3
We study the differential privacy (DP) of a graph shift operator (GSO) when an analyst observes the output of a graph filter. In particular, we study the setting in which the input…
When Does Quality-Aware Multimodal Fusion Matter? A Leakage-Safe Diagnostic for Decision-Level Dependence
Jaden Moon, Arvind Pillai, Andrew Campbell
Many multimodal systems estimate the reliability of each modality and weight their contributions to the final prediction. However, it remains unclear whether these scores influence…
Reconstruction Limits for Repeated Differentially Private Aggregates: A Cramer-Rao Perspective on Query Geometry
Chenyue Zhang, Andrew Campbell, Anna Scaglione +1
Repeated differentially private (DP) releases are often evaluated by transcript length or cumulative privacy accounting. We show that these quantities do not by themselves determin…
Graph Transfer Learning via Shared Latent Geometry: Theory and Applications
Tong Wu, Andrew Campbell, Anna Scaglione
Inference and control in engineered physical systems pay a heavy physics cost at deployment: state estimators, inverse-problem solvers, model-predictive controllers, schedulers, an…
Differentially Private Synthetic Voltage Phasor Release for Distribution Grids
Andrew Campbell, Chenyue Zhang, Anna Scaglione +3
Training machine learning models, including Grid Foundation Models (GFMs), requires large volumes of realistic grid data, yet substantial privacy concerns discourage utilities and…