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Multiscale Geometric Feature Extraction
Mathematics of Data & Decisions| Speaker: | Wolfgang Polonik, UC Davis (Statistics) |
| Related Webpage: | http://www.stat.ucdavis.edu/~polonik/WP-personal-home.html |
| Location: | Zoom Lecture |
| Start time: | Tue, Nov 24 2020, 4:10PM |
A method for extracting multiscale geometric features from a data cloud is presented. Each pair of data points is mapped into a real-valued feature function, whose construction is based on geometric considerations. The collection of these feature functions is then being used for further data analysis. Applications include classification, anomaly detection and data visualization. In contrast to the popular kernel trick, the construction of the feature functions is based on geometric considerations. The performance of the methodology is illustrated through applications to real data sets, and some theoretical guarantees supporting the performance of the novel methodology are presented. This is joint work with G. Chandler.
zoom info available https://sites.google.com/view/maddd After the talk, we will do virtual tea/coffee get-together at https://gather.town/KOoFj0aKT5GkEj40/Alder-Room