69 citations · 88 across the 15 of their papers we have counts for
4 papers · 1 filter
Contraction of -Divergence and Its Applications to Privacy
Shahab Asoodeh, Mario Diaz, Flavio P. Calmon
We investigate the contraction coefficients derived from strong data processing inequalities for the -divergence. By generalizing the celebrated Dobrushin's coefficient from t…
On the alpha-loss Landscape in the Logistic Model
Tyler Sypherd, Mario Diaz, Lalitha Sankar +1
We analyze the optimization landscape of a recently introduced tunable class of loss functions called -loss, , in the logistic model. This family encapsulates t…
To Split or Not to Split: The Impact of Disparate Treatment in Classification
Hao Wang, Hsiang Hsu, Mario Diaz +1
Disparate treatment occurs when a machine learning model yields different decisions for individuals based on a sensitive attribute (e.g., age, sex). In domains where prediction acc…
Privacy Amplification of Iterative Algorithms via Contraction Coefficients
Shahab Asoodeh, Mario Diaz, Flavio P. Calmon
We investigate the framework of privacy amplification by iteration, recently proposed by Feldman et al., from an information-theoretic lens. We demonstrate that differential privac…