D
Daniel S. Hirschberg
Researcher at University of California, Irvine
Publications - 92
Citations - 5553
Daniel S. Hirschberg is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Longest increasing subsequence & Longest common subsequence problem. The author has an hindex of 30, co-authored 92 publications receiving 5323 citations. Previous affiliations of Daniel S. Hirschberg include Princeton University & French Institute for Research in Computer Science and Automation.
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A linear space algorithm for computing maximal common subsequences
TL;DR: The problem of finding a longest common subsequence of two strings has been solved in quadratic time and space and an algorithm is presented which will solve this problem in QuadraticTime and in linear space.
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Algorithms for the Longest Common Subsequence Problem
TL;DR: A lgor i thm is appl icable in the genera l case and requi res O ( p n + n log n) t ime for any input strings o f lengths m and n even though the lower bound on T ime of O ( m n ) need not apply to all inputs.
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Data compression
TL;DR: A variety of data compression methods are surveyed, from the work of Shannon, Fano, and Huffman in the late 1940s to a technique developed in 1986, which has important application in the areas of file storage and distributed systems.
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Bounds on the Complexity of the Longest Common Subsequence Problem
TL;DR: It is shown that unless a bound on the total number of distinct symbols is assumed, every solution to the problem can consume an amount of time that is proportional to the product of the lengths of the two strings.
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Computing connected components on parallel computers
TL;DR: A parallel algorithm which uses n=2 processors to find the connected components of an undirected graph with n vertices in time in time O(n), which can be used to finding the transitive closure of a symmetric Boolean matrix.