Duke Applied Mathematics

Publications [#321991] of John Harer

Papers Published

1. Bendich, P; Gasparovic, E; Harer, J; Izmailov, R; Ness, L, Multi-scale local shape analysis and feature selection in machine learning applications, Proceedings of the International Joint Conference on Neural Networks, vol. 2015-September (September, 2015), IEEE, ISBN 9781479919604 [doi]
   (last updated on 2024/04/23)

   Abstract:
   We introduce a method called multi-scale local shape analysis for extracting features that describe the local structure of points within a dataset. The method uses both geometric and topological features at multiple levels of granularity to capture diverse types of local information for subsequent machine learning algorithms operating on the dataset. Using synthetic and real dataset examples, we demonstrate significant performance improvement of classification algorithms constructed for these datasets with correspondingly augmented features.