activity
20122023
most citedWasserstein Stability of the Entropy Power Inequality for Log-Concave Densities

11 citations · 36 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CR2023

Mean Estimation Under Heterogeneous Privacy Demands

Syomantak Chaudhuri, Konstantin Miagkov, Thomas A. Courtade

Differential Privacy (DP) is a well-established framework to quantify privacy loss incurred by any algorithm. Traditional formulations impose a uniform privacy requirement for all…

cs.CR2023

Mean Estimation Under Heterogeneous Privacy: Some Privacy Can Be Free

Syomantak Chaudhuri, Thomas A. Courtade

Differential Privacy (DP) is a well-established framework to quantify privacy loss incurred by any algorithm. Traditional DP formulations impose a uniform privacy requirement for a…

cs.IT20222 cited

Entropy Inequalities and Gaussian Comparisons

Efe Aras, Thomas A. Courtade

We establish a general class of entropy inequalities that take the concise form of Gaussian comparisons. The main result unifies many classical and recent results, including the Sh…

cs.IT201611 cited

Wasserstein Stability of the Entropy Power Inequality for Log-Concave Densities

Thomas A. Courtade, Max Fathi, Ashwin Pananjady

We establish quantitative stability results for the entropy power inequality (EPI). Specifically, we show that if uniformly log-concave densities nearly saturate the EPI, then they…

q-bio.PE2016

Novel probabilistic models of spatial genetic ancestry with applications to stratification correction in genome-wide association studies

Anand Bhaskar, Adel Javanmard, Thomas A. Courtade +1

Genetic variation in human populations is influenced by geographic ancestry due to spatial locality in historical mating and migration patterns. Spatial population structure in gen…

cs.IT2016

Monotonicity of Entropy and Fisher Information: A Quick Proof via Maximal Correlation

Thomas A. Courtade

A simple proof is given for the monotonicity of entropy and Fisher information associated to sums of i.i.d. random variables. The proof relies on a characterization of maximal corr…