Math @ Duke
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Publications [#225824] of John Harer
Papers Accepted
- P. Bendich, E. Gasparovic, J. Harer, R. Izmailov, and L. Ness, Multi-Scale Local Shape Analysis and Feature Selection in Machine Learning Applications,
AISTATS
(2014)
(last updated on 2014/12/15)
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.
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