SF-GRASS
Author:
Affiliation:
1. Stevens Institute of Technology
2. Michigan Technological University
Funder
Division of Computing and Communication Foundations
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3400302.3415629
Reference33 articles.
1. Randomized Approximation Schemes for Cuts and Flows in Capacitated Graphs
2. T. Davis. <u>CHOLMOD: sparse supernodal Cholesky factorization and update/downdate.</u> [Online]. Available: http://www.cise.ufl.edu/research/sparse/cholmod/ 2008. T. Davis. <u>CHOLMOD: sparse supernodal Cholesky factorization and update/downdate.</u> [Online]. Available: http://www.cise.ufl.edu/research/sparse/cholmod/ 2008.
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1. Unleashing the Power of Graph Spectral Sparsification for Power Grid Analysis via Incomplete Cholesky Factorization;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023-09
2. pGRASS-Solver: A Graph Spectral Sparsification-Based Parallel Iterative Solver for Large-Scale Power Grid Analysis;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023-09
3. Graph Sparsification by Universal Greedy Algorithms;Journal of Computational Mathematics;2023-06
4. SF-SGL: Solver-Free Spectral Graph Learning From Linear Measurements;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023-04
5. HyperEF;Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design;2022-10-30
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