Publications

Found 6 results
Author Title [ Type(Asc)] Year
Filters: First Letter Of Title is A and Author is Michael Carl Tschantz  [Clear All Filters]
Technical Report
Tschantz, M. Carl, Egelman S., Choi J., Weaver N., & Friedland G. (2016).  The Accuracy of the Demographic Inferences Shown on Google's Ad Settings.
Conference Paper
Datta, A., Tschantz M. Carl, & Datta A. (2015).  Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice, and Discrimination. Proceedings on Privacy Enhancing Technologies. 2015(1), 92-112.
Plane, A. C., Redmiles E. M., Mazurek M. L., & Tschantz M. Carl (2017).  Assessing user perceptions of online targeted advertising. Proceedings of USENIX Security 2017.
Arefi, M. Navaki, Pandi R., Tschantz M. Carl, Crandall J. R., Fu K-wa., Shi D. Qiu, et al. (2019).  Assessing Post Deletion in Sina Weibo: Multi-modal Classification of Hot Topics.
Miller, B., Kantchelian A., Afroz S., Bachwani R., Dauber E., Huang L., et al. (2014).  Adversarial Active Learning. Proceedings of the 2014 Workshop on Artificial Intelligent and Security Workshop (AISec '14). 3–14.
Tschantz, M. Carl, Egelman S., Choi J., Weaver N., & Friedland G. (2018).  The Accuracy of the Demographic Inferences Shown on Google's Ad Settings. Proceedings of the 2018 Workshop on Privacy in the Electronic Society. 33-41.