A \Go with the winners" algorithm is easy to implement on the new tree, and the parameter for the new tree is simply poly(d) times the value of for the old tree. that if Algorithm 1 is run with B = poly(d), then it fails to nd the deepest leaf with probability at most 1=4.
We prove that the running time of the "go with the winners” scheme (to achieve 99% probability of success) is bounded by a polynomial in d and . By contrast,.
In this paper, we give a rigorous analysis of such a "go with the winners" scheme in the concrete setting of searching for a deep leaf in a tree.
Algorithm 1. “Go with the winners” Repeat the following procedure, starting at stage 0 with B par- ticles at the root.
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A simple condition is proposed which intends to capture precisely the set of search trees for which the “Go With The Winners” algorithm will find a deepest ...
Go-with-the-winners (GWW) was introduced by Aldous and Vazirani [AV94] as a new paradigm for designing heuristics for NP-hard problems. The main idea behind GWW ...
We introduce a variant of the following "Go with the winners" strategy that can be used directly in combinatorial optimization: Many particles randomly search ...
In this paper, we give a rigorous analysis of such a "go with the winners" scheme in the concrete setting of searching for a deep leaf in a tree. There are two ...
The main contribution of this paper is an algorithm which parallelizes the 'go with the winners' scheme of Aldous and Vazirani. We prove that, under reasonable ...
Go with the Winners Algorithms: A Rigorous Analysis and a New Framework for Optimization. Author, Anastasios D. Dimitriou. Publisher, University of California ...