Article ID Journal Published Year Pages File Type
10334261 Theoretical Computer Science 2005 14 Pages PDF
Abstract
In this setting, we suggest randomized subexponential algorithms appropriate for RLG- and PRLG-function optimization. We show that the subexponential algorithms for combinatorial linear programming, due to Kalai and Matoušek, Sharir, Welzl, can be adapted for optimizing the RLG- and PRLG-functions.
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Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
Preview
Combinatorial structure and randomized subexponential algorithms for infinite games
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