SIAM Journal on Computing
Making data structures persistent
Journal of Computer and System Sciences - 18th Annual ACM Symposium on Theory of Computing (STOC), May 28-30, 1986
A new upper bound on the complexity of the all pairs shortest path problem
Information Processing Letters
An optimal algorithm for selection in a min-heap
Information and Computation
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
SIAM Journal on Computing
Algorithms for the maximum subarray problem based on matrix multiplication
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Programming pearls: algorithm design techniques
Communications of the ACM
Data Mining with optimized two-dimensional association rules
ACM Transactions on Database Systems (TODS)
Improved Algorithms for the K-Maximum Subarray Problem
The Computer Journal
Improved algorithmms for the k maximum-sums problems
Theoretical Computer Science
Journal of Computer and System Sciences
Improved algorithms for the K-maximum subarray problem for small K
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
Randomized algorithm for the sum selection problem
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
Efficient algorithms for k maximum sums
ISAAC'04 Proceedings of the 15th international conference on Algorithms and Computation
Optimal algorithms for the average-constrained maximum-sum segment problem
Information Processing Letters
A sub-cubic time algorithm for the k-maximum subarray problem
ISAAC'07 Proceedings of the 18th international conference on Algorithms and computation
Journal of Discrete Algorithms
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Finding the sub-vector with the largest sum in a sequence of n numbers is known as the maximum sum problem. Finding the k sub-vectors 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 two-dimensional k maximal sums problem in O(m2 ċ n+k) time, where the input is an m × n matrix with m ≤ n. We generalize this algorithm to solve the d-dimensional problem in O(n2d-1+ k) time. The space usage of all the algorithms can be reduced to O(nd-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.