Kirk L. Kroeker
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Abstract
Computer scientists at Carnegie Mellon University have devised an algorithm that might be able to solve a certain class of linear systems much more quickly than today's fastest solvers.
- Koutis, I., Miller, G.L., and Peng, R. Approaching optimality for solving SDD linear systems, Proceedings of the 2010 IEEE 51st Annual Symposium on Foundations of Computer Science, Las Vegas, NV, Oct. 23-26, 2010. Google Scholar
Digital Library
- Spielman, D.A. and Teng, S-H. Nearly-linear time algorithms for graph partitioning, graph sparsification, and solving linear systems, Proceedings of the 36th Annual ACM Symposium on Theory of Computing, Chicago, IL, June 13-16, 2004. Google ScholarDigital Library
- Koutis, I., Miller, G.L., and Tolliver, D. Combinatorial preconditioners and multilevel solvers for problems in computer vision and image processing, Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I, Las Vegas, NV, Nov. 30-Dec. 2, 2009. Google ScholarDigital Library
- Blelloch, G.E., Koutis, I., Miller, G.L., and Tangwongsan, K. Hierarchical diagonal blocking and precision reduction applied to combinatorial multigrid, Proceedings of the 2010 ACM/ IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, New Orleans, LA, Nov. 13-19, 2010. Google ScholarDigital Library
- Teng, S.-H. The Laplacian paradigm: Emerging algorithms for massive graphs. Lecture Notes in Computer Science 6108, Kratochvíl, J., Li, A., Fiala, J., and Kolman, P. (Eds.), Springer-Verlag, Berlin, Germany, 2010. Google ScholarDigital Library
Index Terms
- A breakthrough in algorithm design
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