Computational geometry plays a crucial and natural role in interacting with machine learning. Since geometric algorithms often come with quality guaranteed solutions, they are of ciritical importance in formalizing the effectiveness of various techniques and in developing new ones. On the other hand, problems in machine learning serve as important motivation for work central to geometric algorithms. This workshop is intended to provide a forum for those working in the fields of computational geometry, algorithms, machine learning and the various theoretical and algorithmic challenges to promote their interplay. As a joint STOC/SoCG workshop, we hope researchers who normally frequent only one of STOC or SoCG, but work in geometric algorithms for machine learning, will converge together sharing their insights and developments.
We are soliciting short papers (2-6 pages), presentations, project demos, or tutorials on any of the following topics: