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- W1547954018 abstract "Stochastic algorithms are among the best for solving computationally hard search and reasoning problems. The runtime of such procedures is characterized by a random variable. Different algorithms give rise to different probability distributions. One can take advantage of such differences by combining several algorithms into a portfolio, and running them in parallel or interleaving them on a single processor. We provide a detailed evaluation of the portfolio approach on distributions of hard combinatorial search problems. We show under what conditions the protfolio approach can have a dramatic computational advantage over the best traditional methods." @default.
- W1547954018 created "2016-06-24" @default.
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- W1547954018 date "2013-02-06" @default.
- W1547954018 modified "2023-09-27" @default.
- W1547954018 title "Algorithm Portfolio Design: Theory vs. Practice" @default.
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