Antonella Zanobetti, Patrick H Ryan, Brent A Coull, Heike Luttmann-Gibson, Soma Datta, Jeffrey Blossom, Cole Brokamp, Nathan Lothrop, Rachel L Miller, Paloma I Beamer, Cynthia M Visness, Howard Andrews, Leonard B Bacharier, Tina Hartert, Christine C Johnson, Dennis R Ownby, Gurjit K Khurana Hershey, Christine L M Joseph, Eneida A Mendonça, Daniel J Jackson, Edward M Zoratti, Anne L Wright, Fernando D Martinez, Christine M Seroogy, Sima K Ramratnam, Agustin Calatroni, James E Gern, Diane R Gold
Early-Life Exposure to Air Pollution and Childhood Asthma Cumulative Incidence in the ECHO CREW Consortium
JAMA network open
differential privacy mathematical concept provides informationtheoretic security guarantee differential privacy emerged de facto standard guaranteeing privacy data sharing known mechanisms achieve come serious limitations utility guarantees usually provided fixed priori specified set queries moreover utility guarantees complexbut commonmachine learning tasks clustering classification paper overcome limitations working metric privacy powerful generalization differential privacy develop polynomialtime algorithm creates private measure data set private measure allows us efficiently construct private synthetic data accurate wide range statistical analysis tools moreover prove asymptotically sharp minmax result private measures synthetic data general compact metric spaces fixed privacy budget bounded away zero key ingredient construction new superregular random walk whose joint distribution steps regular independent random variables yet deviates origin logarithmically slowly