Learning problems that involve combinatorial objects are ubiquitous - they include the prediction of graphs, assignments, rankings, trees, groups of discrete labels or preferred sets of a user; the expression of prior structural knowledge for regularization, the identification of sets of important variables, or inference in discrete probabilistic models.
On May 10 and 11, Jonas Peters (University of Copenhagen) gave four lectures on causality. Slides and videos are available.
Youssef Marzouk aims to improve predictions of everything from underground pollution to daily weather.
SDSCon 2017 gathers community and showcases research projects that apply data science to major systems and issues