| B. Ravikumar, K. Ganesan and K. B. Lakshmanan. " On selecting the largest element in spite of erroneous information ". Lecture Notes in Computer Science, ICALP 1987, 88-99. |
....on asymptotic results and our constants are sometimes very large. Nevertheless, we believe that our results do provide insights into the design of real world playoff systems. 2 Previous Results The problem of selecting the best of n players using unreliable comparisons was addressed in [RGL], where Ravikumar, Ganesan and Lakshmanan assume that the total number of erroneous outcomes is less than some absolute upper bound e. They show that (e 1)n Gamma 1 comparisons are necessary and sufficient to find the best player. In [FPRU] Feige, Peleg, Raghavan and Upfal choose a ....
B. Ravikumar, K. Ganesan and K. B. Lakshmanan. " On selecting the largest element in spite of erroneous information ". Lecture Notes in Computer Science, ICALP 1987, 88-99.
....of (em=d) d [BEHW89] when d is large relative to m, which is useful for this application. Note that if E 2 Omega Gamma212 n) the En term in our sorting bound of O(n log n En) dominates. This is especially interesting in light of the result of Ravikumar, Ganesan and Lakshmanan [RGL87] which says that (E 1)n Gamma 1 comparisons are necessary and 1 In this paper, we follow usual convention of denoting the base 2 logarithm by log and the natural logarithm by ln. 2 Bounds of O(log n E) on the first minimum of this theorem were obtained independently by CesaBianchi and ....
B. Ravikumar, K. Ganesan, and K.B. Lakshmanan. On selecting the largest element in spite of erroneous information. Proceedings of STACS87, Lecture Notes in Computer Science, 247, 1987.
....on asymptotic results and our constants are sometimes very large. Nevertheless, we believe that our results do provide insights into the design of real world playoff systems. 2 Previous Results The problem of selecting the best of n players using unreliable comparisons was addressed in [RGL], where Ravikumar, Ganesan and Lakshmanan assume that the total number of erroneous outcomes is less than some absolute upper bound e. They show that (e 1)n Gamma 1 comparisons are necessary and sufficient to find the best player. In [FPRU] Feige, Peleg, Raghavan and Upfal choose a ....
B. Ravikumar, K. Ganesan and K. B. Lakshmanan. " On selecting the largest element in spite of erroneous information ". Lecture Notes in Computer Science, ICALP 1987, 88-99.
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B. Ravikumar, K. Ganesan, and K. B. Lakshmanan, "On selecting the largest element in spite of erroneous information", Proceedings of ICALP '87, 88-99.
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