Finding the local minimum with sublinear time

Jan 17, 2012 · In this paper, we give the first algorithm for this problem that uses the optimum number of measurements (up to constant factors) and runs in sublinear time o(N) when k is sufficiently less than N. Specifically, for any positive integer l , our approach uses time O ( l 5 ε -3 k ( N/k ) 1/ l ) and uses m = O ( l 8 ε -3 k log( N/k ...

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  • Play store app download versionThe analogous theorem in the continuous time case is the Doob-Meyer decomposition theorem proved by Meyer in [8, 9]. For the pricing American option problem in incomplete market, Kramkov constructs the optional decomposition of supermartingale with respect to a family of equivalent local martingale measures. He calls such a representation ...

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  • Reddit ammo 2020Constant time algorithms are a subclass of sublinear time algorithms. They work not only in sublinear time with respect to the input size but also in constant time. The proposed algorithm is classified as a constant time approximation algorithm. The examples of sublinear time approximation algorithms include minimum spanning tree in metric

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  • Output: Index of a local minima is 2 Time Complexity : O(Log n) Related Problem : Find a peak element. This article is contributed by Roshni Agarwal.If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to [email protected] See your article appearing on the GeeksforGeeks main page and help other ...
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  • Stiropor lajsni mk$\begingroup$ The k-d tree is indeed relevant, but there are no guarantees that you can find the nearest neighbor in logarithmic lookup time -- in fact, the lookup time can be arbitrarily bad. You might be thinking of results that if the points in the database are randomly distributed then finding a nearest neighbor might take logarithmic time (I can't personally vouch for that), but that's a ...

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  • Mar 18, 2020 · Local minimum in an array. Write a program that, given an array a[] of n distinct integers, finds a local minimum: an index i such that botha[i] a[i-1] and a[i] a[i+1] (assuming the neighboring entry is in bounds). Your program should use ~ 2 lg n compares in the worst case.
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