Topological data analysis and machine learning theory (12w5081)
Gunnar Carlsson (Stanford University)
Dmitry Feichtner-Kozlov (Bremen University)
Rick Jardine (University of Western Ontario)
Dmitriy Morozov (Lawrence Berkeley National Laboratory)
While the fields address closely related questions, it is not yet common for the researchers from the different disciplines to meet: there are no regular joint conferences. The mutual benefit of such meeting is clear. Machine learning techniques employ geometry and topology, and, therefore, would benefit from the latest developments. Topologists, in turn, gain from learning about the current state of the art in machine learning, and better aligning their work with the current developments in the parallel field.
Our aim is to create an opportunity for the different groups to gather, identify shared interests, complementary challenges, and promising areas of collaboration.