Mini course by Yasu Hiraoka:
"Research topics on random topology, machine learning, and persistent homology."
November 13 to 15, 2017.

Organization

Description: A mini course by Yasu Hiraoka about "Research topics on random topology, machine learning, and persistent homology".

In this series of lectures, Prof. Hiraoka will present several research topics on random topology and machine learning on persistent homology signatures. Persistent homology is one of the important tools in topological data analysis and it characterizes shapes of data. In particular, it provides a tool called the persistence diagram that extracts multiscale topological features such as rings and cavities in data (e.g. atomic configurations, high dimensional digital images etc).

Location and Times: See below.

Contact: Matthew Kahle, mkahle@math.osu.edu.

Support: MRI and NSF-RTG.

Schedule

• Monday, November 13 . Lecture 1: Convergence of persistence diagrams on stationary point process in R^N. Time and Location: 3:00pm to 4:00pm, Cunz Hall 180. Abstract.
• Tuesday, November 14th. Lecture 2: A higher dimensional generalization of Frieze's zeta(3) theorem on the Linial-Meshulam process and the clique complex process. Time and Location: 4--5PM, Journalism Building 251. Abstract.
• Wednesday, November 15th. Lecture 3: Applications of persistent homology to materials science. Time and Location: 11-12, Enarson Classroom Bldg 222. Abstract.