D. Aldous and U. Vazirani, Go With the Winners Algorithms. In Proc. 35th Symp. Foundations of Computer Sci., pages 492-501, 1994. Home/Search Document Details and Download
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Co-Evolving Heuristics and the Problems They Solve - Belew, Carson, Impagliazzo, .. (1999) (Correct)
....subspaces containing solutions satisfying a progressively more stringent threshold. GWW also restricts itself to local, mutation like operators for the generation of new particles to be explored. These characteristics have made a theoretic analysis of population based search in GWWs possible [D.Aldous, 1994, A.Dimitriou, 1996, A.Dimitriou, 1998] GWW therefore provides a useful touchstone for a theoretic foundation for GAs. The most extensive empirical analysis of GWWs have involved the minimum graph bisection problem [A.Dimitriou, 1998, Given a graph V; E (with jV j even) find a ....
D.Aldous, U. Vazirani (1994). Go with the winners' algorithms. In Proceedings of the 35th IEEE Symposium on Foundations of Computer Science, pages 492--501.
Multiagent Cooperative Search for Portfolio Selection - Parkes, Huberman (2 citations) (Correct)
.... algorithms (Rao and Kumar, 1993; Luby and Ertel, 1993; Kauffman and Levin, 1987; Kornfeld, 1981; Huberman et al. 1997) Knight (1993) compares the performance of a system of many cooperative agents with simple search heuristics to a system of a few agents with more complex search heuristics, and Aldous and Vazirani (1994) describe a cooperative search technique that they term Go with the winners . Schaerf et al. 1995) study communication between agents in a load balancing system where agents are in direct competition for resources. They show that when agents exchange information on resource loading with other ....
Aldous, D., and Vazirani, U. (1994). "Go with the winners algorithms," in Proc. of the 35th Symp.
Learning as Applied to Simulated Annealing - Su, Buntine, Newton (Correct)
....results and in Section 5 we present our conclusions and area for future work. 2. SIMULATED ANNEALING AND REGRESSION A number of definitions are introduced below for use in presenting the overall approach. Page 3 2. 1 Simulated Annealing There are many versions of the simulated annealing [14, 17 19]. We will outline the basic framework of the algorithm below. If S represents a particular configuration of the placement, T is the current temperature of the annealing, S C returns the cost of configuration S, m is a move (in our case, a two cell swap) S is the new configuration due to the ....
David Aldous and Umesh Vazirani, "Go with the winners algorithms", Proceedings. 35th Annual Symposium on Foundations of Computer Science, pp.492-501, 1994
Y.M. Zhang and X.R. Li. Detection and diagnostic of.. - Viens Portfolio.. (Correct)
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D. Aldous and U. Vazirani, Go With the Winners Algorithms. In Proc. 35th Symp. Foundations of Computer Sci., pages 492-501, 1994.
Empirical and Analytic Approaches to Understanding Local Search.. - Carson (2001) (Correct)
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D. Aldous, and U. Vazirani. Go with the winners algorithms. In Proceedings of the 35th IEEE Symposium on Foundations of Computer Science, pages 492--501, 1994.
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