Machine learning has enabled tremendously exciting technologies, but at the same time it raises questions as to how it should be deployed in a responsible and trustworthy manner. How can machine learning be made secure, reliable, robust, fair, and private? This workshop will explore the information-theoretic foundations of these aspects of machine learning. The workshop will include invited talks by experts on these topics from both academy and industry, student poster presentations, and time for fruitful discussions. Keynote talks will be given by Tara Javidi, Ilya Mironov, Todd Coleman, and Ayfer Ozgur.
Co-Organizers: Lalitha Sankar (Arizona State University), Flavio Calmon (Harvard), Oliver Kosut (Arizona State University)