12 citations · 12 across the 4 of their papers we have counts for
4 papers
SAFES: Sequential Privacy and Fairness Enhancing Data Synthesis for Responsible AI
Spencer Giddens, Xiaon Lang, Fang Liu
As data-driven and AI-based decision making gains widespread adoption across disciplines, it is crucial that both data privacy and decision fairness are appropriately addressed. Al…
DPpack: An R Package for Differentially Private Statistical Analysis and Machine Learning
Spencer Giddens, Fang Liu
Differential privacy (DP) is the state-of-the-art framework for guaranteeing privacy for individuals when releasing aggregated statistics or building statistical/machine learning m…
A Differentially Private Weighted Empirical Risk Minimization Procedure and its Application to Outcome Weighted Learning
Spencer Giddens, Yiwang Zhou, Kevin R. Krull +3
Data used to train predictive models via empirical risk minimization (ERM) often contain sensitive personal information. While differential privacy (DP) provides mathematically pro…
Methodological reconstruction of historical seismic events from anecdotal accounts of destructive tsunamis: a case study for the great 1852 Banda arc mega-thrust earthquake and tsunami
Hayden Ringer, Jared P. Whitehead, Justin Krometis +14
We demonstrate the efficacy of a Bayesian statistical inversion framework for reconstructing the likely characteristics of large pre-instrumentation earthquakes from historical rec…