Adam Christopher Wilkerson

Works (2)

Updated: April 11th, 2023 10:13

2014 conference paper

Computing persistent features in big data: A distributed dimension reduction approach

International conference on acoustics speech and signal processing.

By: A. Wilkerson n, H. Chintakunta n & H. Krim n

TL;DR: A simplicial collapse algorithm called the selective collapse is developed by representing the previously developed strong collapse as a forest and uses that forest data to improve the speed of both the strong collapse and of persistent homology. (via Semantic Scholar)
Source: NC State University Libraries
Added: August 6, 2018

2013 conference paper

Simplifying the homology of networks via strong collapses

International conference on acoustics speech and signal processing, 5258–5262.

By: A. Wilkerson n, T. Moore *, A. Swami* & H. Krim n

TL;DR: A novel algorithm is detailed for simplifying homology and “hole location” computations on a complex by reducing it to its core using a strong collapse, which leads to significant savings in complexity. (via Semantic Scholar)
Source: NC State University Libraries
Added: August 6, 2018

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