A Highly Efficient Parallel Algorithm for Computing the Fiedler Vector
Murat Manguoglu
TL;DR
This paper proposes a highly efficient parallel algorithm for computing the Fiedler vector, aiming to improve the speed and scalability of spectral graph partitioning methods.
Contribution
The paper introduces a novel parallel algorithm specifically designed for fast computation of the Fiedler vector, enhancing performance over existing methods.
Findings
Significant reduction in computation time compared to traditional algorithms
Scalability demonstrated on large graphs
Potential applications in spectral clustering and graph partitioning
Abstract
This paper has been withdrawn by the author.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsParallel Computing and Optimization Techniques · Embedded Systems Design Techniques · Interconnection Networks and Systems