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Journal ArticleDOI

A lower-variance randomized algorithm for approximate string matching

Mikhail J. Atallah, +2 more
- 01 Sep 2013 - 
- Vol. 113, Iss: 18, pp 690-692
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TLDR
This paper provides an algorithm that also runs in deterministic time O(kNlogM) but achieves a lower variance of min(M/k, M-c)(M-c)/k, which is essentially a factor of k smaller than in previous work.
About
This article is published in Information Processing Letters.The article was published on 2013-09-01. It has received 15 citations till now. The article focuses on the topics: Bias of an estimator & Approximate string matching.

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Citations
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Journal ArticleDOI

Fast Detection of Transformed Data Leaks

TL;DR: This paper utilizes sequence alignment techniques for detecting complex data-leak patterns and achieves good detection accuracy in recognizing transformed leaks, and implements a parallelized version of the algorithms in graphics processing unit that achieves high analysis throughput.
Book ChapterDOI

Entropic Trace Estimates for Log Determinants

TL;DR: This work estimates log determinants under the framework of maximum entropy, given information in the form of moment constraints from stochastic trace estimation, demonstrating a significant improvement on state-of-the-art alternative methods.
Book ChapterDOI

Optimal Query Complexity for Estimating the Trace of a Matrix

TL;DR: In this paper, the authors studied the query complexity of randomized algorithms for estimating the trace of an implicit n×n matrix and showed that any estimator requires Ω(1/e) queries to have a guarantee of variance at most.
Journal ArticleDOI

On approximate pattern matching with thresholds

TL;DR: The main result of this paper is to show that this threshold version of the problem can be solved by recursively solving 3 + 2 log ⁡ θ instances of the traditional (i.e., zero-threshold) version of this problem, which is much-studied in the literature and for which there are many efficient (typically randomized) solutions of time complexity close to O.
Proceedings ArticleDOI

Breaking the Variance: Approximating the Hamming Distance in 1/a#x3B5; Time Per Alignment

TL;DR: The main idea behind the algorithm is to reduce the variance of a specific randomized experiment by (approximately) separating heavy hitters from non-heavy hitters, and it is shown that this belief that obtaining an algorithm for solving the approximation version cannot be done much faster as a function of 1/ε is false.
References
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Journal ArticleDOI

Efficient string matching: an aid to bibliographic search

TL;DR: A simple, efficient algorithm to locate all occurrences of any of a finite number of keywords in a string of text that has been used to improve the speed of a library bibliographic search program by a factor of 5 to 10.
Journal ArticleDOI

A new approach to text searching

TL;DR: A family of simple and fast algorithms for solving the classical string matching problem, string matching with don't care symbols and complement symbols, and multiple patterns are introduced.

String-matching and other products

TL;DR: By exploiting the formal similarity of string-matching with integer multiplication, a new algorithm has been obtained with a running time which is only slightly worse than linear.
Journal ArticleDOI

Generalized string matching

TL;DR: A generalization of string matching, in which the pattern is a sequence of pattern elements, each compatible with a set of symbols, is investigated, which shows that generalized string matching requires a time-space product of $\Omega ({{n^2 } / {\log n}})$ on a powerful model of computation, when the alphabet is restricted to n symbols.
Book

Efficient String Matching With K Mismatches

TL;DR: An algorithm for finding all occurrences of the pattern in the text, each with at most k mismatches, runs in O( k ( m log m + n )) time.