Applications of a strategy for designing divide-and-conquer algorithms
Science of Computer Programming
Introduction to algorithms
Programming pearls: perspective on performance
Communications of the ACM
Programming pearls: algorithm design techniques
Communications of the ACM
A Linear Time Algorithm for Finding All Maximal Scoring Subsequences
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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
Fast algorithms for finding disjoint subsequences with extremal densities
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
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Given a sequence, the problem studied in this paper is to find a set of k disjoint continuous subsequences such that the total sum of all elements in the set is maximized. This problem arises naturally in the analysis of DNA sequences. The previous best known algorithm requires Θ(n log n) time in the worst case. For a given sequence of length n, we present an almost linear-time algorithm for this problem. Our algorithm uses a disjoint-set data structure and requires O(nα(n, n)) time in the worst case, where α(n, n) is the inverse Ackermann function.