Efficient Optimization of Dominant Set Clustering with Frank-Wolfe Algorithms
Abstract
We study Frank-Wolfe algorithms - standard, pairwise, and away-steps - for efficient optimization of Dominant Set Clustering. We present a unified and computationally efficient framework to employ the different variants of Frank-Wolfe methods, and we investigate its effectiveness via several experimental studies. In addition, we provide explicit convergence rates for the algorithms in terms of the so-called Frank-Wolfe gap. The theoretical analysis has been specialized to Dominant Set Clustering and covers consistently the different variants.
Keywords
Cite
@article{arxiv.2007.11652,
title = {Efficient Optimization of Dominant Set Clustering with Frank-Wolfe Algorithms},
author = {Carl Johnell and Morteza Haghir Chehreghani},
journal= {arXiv preprint arXiv:2007.11652},
year = {2022}
}
Comments
Accepted at CIKM 2022. Sole copyright holder is ACM - CIKM (ACM International Conference on Information & Knowledge Management), all rights reserved. Available at https://dl.acm.org/doi/10.1145/3511808.3557306