Part of the Lecture Notes in Computer Science book series (LNCS, volume 1663)
Go-with-the-winners (GWW) is a simple but powerful paradigm for designing heuristics for NP-hard optimization problems. We give a brief survey of the theoretical basis as well as the experimental validation of this paradigm.
KeywordsRandom Graph Edge Density Geometric Graph Local Expansion 35th IEEE Symposium
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
- [AV94]Aldous, D., Vazirani, U.: “Go with the winners” Algorithms. Proceedings of 35th IEEE Symposium on Foundations of Computer Science (FOCS), pages 492–501, 1994.Google Scholar
- [CI99]Carson, T., Impagliazzo, R.: Experimentally Determining Regions of Related Solutions for Graph Bisection Problems. Manuscript, 1999.Google Scholar
- [DI96]Dimitriou, A., Impagliazzo, R.: Towards a Rigorous Analysis of Local Optimization Algorithms. 28th ACM Symposium on the Theory of Computing, 1996.Google Scholar
- [DI98]Dimitriou, A., Impagliazzo, R.: Go-with-the-winners Algorithms for Graph Bisection. SODA 98, pages 510–520, 1998.Google Scholar
© Springer-Verlag Berlin Heidelberg 1999