This position paper discusses the use of machine learning methods in layout design. Interactive layouts are pervasive and a central part of e.g. GUIs, Web interfaces, menus and forms. They have been hard to design algorithmically because search spaces are large and multiple factors contributing to design choices. We argue that in order to touch base with real design practices, machine learning approaches should take into account the requirements posed by user-centered design. We have identified four touch points to user-centered design. For each touch point we discuss both opportunities and challenges and show results from our on-going work.

Citation: Koch, Janin, Weir, Daryl and Antti Oulasvirta. "Learning Layout Design: Challenges and Opportunities." Workshop paper CHI Conference Extended Abstracts on Human Factors in Computing Systems. ACM, 2016.

Paper Download: Learning Layout Design: Challenges and Opportunities