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A Linear Time Algorithm for the k Maximal Sums Problem
"... Abstract. Finding the subvector with the largest sum in a sequence of n numbers is known as the maximum sum problem. Finding the k subvectors with the largest sums is a natural extension of this, and is known as the k maximal sums problem. In this paper we design an optimal O(n+k) time algorithm f ..."
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Abstract. Finding the subvector with the largest sum in a sequence of n numbers is known as the maximum sum problem. Finding the k subvectors with the largest sums is a natural extension of this, and is known as the k maximal sums problem. In this paper we design an optimal O(n+k) time algorithm for the k maximal sums problem. We use this algorithm to obtain algorithms solving the twodimensional k maximal sums problem in O(m 2 ·n+k) time, where the input is an m ×n matrix with m ≤ n. We generalize this algorithm to solve the ddimensional problem in O(n 2d−1 +k) time. The space usage of all the algorithms can be reduced to O(n d−1 + k). This leads to the first algorithm for the k maximal sums problem in one dimension using O(n + k) time and O(k) space. 1
Ranking Cartesian Sums and Kmaximum subarrays
, 2006
"... We design a simple algorithm that ranks K largest in Cartesian sums X + Y in O(m + K log K) time. Based on this, Kmaximum subarrays can be computed in O(n + K log K) time (1D) and O(n 3 + K log K) time (2D) for input array of size n and n × n respectively. 1 ..."
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We design a simple algorithm that ranks K largest in Cartesian sums X + Y in O(m + K log K) time. Based on this, Kmaximum subarrays can be computed in O(n + K log K) time (1D) and O(n 3 + K log K) time (2D) for input array of size n and n × n respectively. 1
A Subcubic Time Algorithm for the kMaximum Subarray Problem
"... Abstract. We design a faster algorithm for the kmaximum subarray problem under the conventional RAM model, based on distance matrix multiplication (DMM). Specifically we achieve O(n 3 √ log log n/log n + k log n) for a general problem where overlapping is allowed for solution arrays. This complexi ..."
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Abstract. We design a faster algorithm for the kmaximum subarray problem under the conventional RAM model, based on distance matrix multiplication (DMM). Specifically we achieve O(n 3 √ log log n/log n + k log n) for a general problem where overlapping is allowed for solution arrays. This complexity is subcubic when k = o(n 3 / log n). The best known complexities of this problem are O(n 3 + k log n), which is cubic when k = O(n 3 /log n), and O(kn 3 √ log log n / log n), which is subcubic when k = o ( √ log n / log log n). 1
Contents lists available at ScienceDirect Information Processing Letters
"... www.elsevier.com/locate/ipl Optimal algorithms for the averageconstrained maximumsum segment problem ..."
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www.elsevier.com/locate/ipl Optimal algorithms for the averageconstrained maximumsum segment problem
Queries and Fault Tolerance
"... The focus of this dissertation is on algorithms, in particular data structures that give provably efficient solutions for sequence analysis problems, range queries, and fault tolerant computing. The work presented in this dissertation is divided into three parts. In Part I we consider algorithms for ..."
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The focus of this dissertation is on algorithms, in particular data structures that give provably efficient solutions for sequence analysis problems, range queries, and fault tolerant computing. The work presented in this dissertation is divided into three parts. In Part I we consider algorithms for a range of sequence analysis problems that have risen from applications in pattern matching, bioinformatics, and data mining. On a high level, each problem is defined by a function and some constraints and the job at hand is to locate subsequences that score high with this function and are not invalidated by the constraints. Many variants and similar problems have been proposed leading to several different approaches and algorithms. We consider problems where the function is the sum of the elements in the sequence and the constraints only bound the length of the subsequences considered. We give optimal algorithms for several variants of the problem based on a simple idea and classic algorithms and data structures. In Part II we consider range query data structures. This a category of