Robust Deep Reinforcement Learning through Bootstrapped Opportunistic Curriculum

BIO

Junlin Wu is a third-year Computer Science Ph.D. student at Washington University in St. Louis. She received her M.S. in Mathematical Finance from Boston University and her B.S. in Mathematics from the University of Science and Technology of China, School of the Gifted Young. Her research has been focusing on adversarial AI, trustworthy reinforcement learning and control, with work published on ICML, IJCAI and GameSec.

How Does Usable Security (Not) End Up in Software Products? Results From a Qualitative Interview Study

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ABSTRACT

In 25 semi-structured interviews with experienced software professionals, including software developers, architects, and designers, we investigate how software products' usable security is implemented during the development process.

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