In alphabetical order:
$(\varepsilon, \delta)$-differential privacy of Gibbs posteriors
Kentaro Minami, Hiromi Arai and Issei Sato [pdf]
Alter-CNN: an approach for learning from label proportions with the application to ice-water Classification
Fan Li and Graham Taylor [pdf]
Bridging weak supervision and privacy aware learning via sufficient statistics
Giorgio Patrini, Frank Nielsen and Richard Nock [pdf]
DUAL-LOCO: Preserving privacy between features in distributed estimation
Christina Heinze, Brian McWilliams and Nicolai Meinshausen [pdf]
Learning with differential privacy: stability, learnability and the sufficiency and necessity of ERM principle
Yu-Xiang Wang, Jing Lei and Stephen E. Fienberg [pdf]
Message passing for collective graphical models
Tao Sun, Daniel Sheldon and Akshat Kumar [pdf]
Private approximations of the 2nd-moment matrix using existing techniques in linear regression
Or Sheffet [pdf]
Private posterior distributions from variational approximations
Vishesh Karwa, Daniel Kifer and Aleksandra Slavkovic [pdf]