New sublinear methods in the struggle against classical problems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.

Bibliographic Details
Main Author: Onak, Krzysztof (Krzysztof Piotr)
Other Authors: Ronitt Rubinfeld.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2011
Subjects:
Online Access:http://hdl.handle.net/1721.1/62428
_version_ 1826194948067688448
author Onak, Krzysztof (Krzysztof Piotr)
author2 Ronitt Rubinfeld.
author_facet Ronitt Rubinfeld.
Onak, Krzysztof (Krzysztof Piotr)
author_sort Onak, Krzysztof (Krzysztof Piotr)
collection MIT
description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
first_indexed 2024-09-23T10:04:21Z
format Thesis
id mit-1721.1/62428
institution Massachusetts Institute of Technology
language eng
last_indexed 2024-09-23T10:04:21Z
publishDate 2011
publisher Massachusetts Institute of Technology
record_format dspace
spelling mit-1721.1/624282019-04-10T18:11:31Z New sublinear methods in the struggle against classical problems Onak, Krzysztof (Krzysztof Piotr) Ronitt Rubinfeld. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 129-134). We study the time and query complexity of approximation algorithms that access only a minuscule fraction of the input, focusing on two classical sources of problems: combinatorial graph optimization and manipulation of strings. The tools we develop find applications outside of the area of sublinear algorithms. For instance, we obtain a more efficient approximation algorithm for edit distance and distributed algorithms for combinatorial problems on graphs that run in a constant number of communication rounds. Combinatorial Graph Optimization Problems: The graph optimization problems considered by us include vertex cover, maximum matching, and dominating set. A graph algorithm is traditionally called a constant-time algorithm if it runs in time that is a function of only the maximum vertex degree, and in particular, does not depend on the number of vertices in the graph. We show a general local computation framework that allows for transforming many classical greedy approximation algorithms into constant-time approximation algorithms for the optimal solution size. By applying the framework, we obtain the first constant-time algorithm that approximates the maximum matching size up to an additive En, where E is an arbitrary positive constant, and n is the number of vertices in the graph. It is known that a purely additive En approximation is not computable in constant time for vertex cover and dominating set. We show that nevertheless, such an approximation is possible for a wide class of graphs, which includes planar graphs (and other minor-free families of graphs) and graphs of subexponential growth (a common property of networks). This result is obtained via locally computing a good partition of the input graph in our local computation framework. The tools and algorithms developed for these problems find several other applications: " Our methods can be used to construct local distributed approximation algorithms for some combinatorial optimization problems. " Our matching algorithm yields the first constant-time testing algorithm for distinguishing bounded-degree graphs that have a perfect matching from those far from having this property. " We give a simple proof that there is a constant-time algorithm distinguishing bounded-degree graphs that are planar (or in general, have a minor-closed property) from those that are far from planarity (or the given minor-closed property, respectively). Our tester is also much more efficient than the original tester of Benjamini, Schramm, and Shapira (STOC 2008). Edit Distance. We study a new asymmetric query model for edit distance. In this model, the input consists of two strings x and y, and an algorithm can access y in an unrestricted manner (without charge), while being charged for querying every symbol of x. We design an algorithm in the asymmetric query model that makes a small number of queries to distinguish the case when the edit distance between x and y is small from the case when it is large. Our result in the asymmetric query model gives rise to a near-linear time algorithm that approximates the edit distance between two strings to within a polylogarithmic factor. For strings of length n and every fixed E > 0, the algorithm computes a (log n)0(/0) approximation in n1i' time. This is an exponential improvement over the previously known near-linear time approximation factor 20( log (Andoni and Onak, STOC 2009; building on Ostrovsky and Rabani, J. ACM 2007). The algorithm of Andoni and Onak was the first to run in O(n 2 -) time, for any fixed constant 6 > 0, and obtain a subpolynomial, n"(o), approximation factor, despite a sequence of papers. We provide a nearly-matching lower bound on the number of queries. Our lower bound is the first to expose hardness of edit distance stemming from the input strings being "repetitive", which means that many of their substrings are approximately identical. Consequently, our lower bound provides the first rigorous separation on the complexity of approximation between edit distance and Ulam distance. by Krzysztof Onak. Ph.D. 2011-04-25T15:57:11Z 2011-04-25T15:57:11Z 2010 2010 Thesis http://hdl.handle.net/1721.1/62428 710993078 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 134 p. application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Onak, Krzysztof (Krzysztof Piotr)
New sublinear methods in the struggle against classical problems
title New sublinear methods in the struggle against classical problems
title_full New sublinear methods in the struggle against classical problems
title_fullStr New sublinear methods in the struggle against classical problems
title_full_unstemmed New sublinear methods in the struggle against classical problems
title_short New sublinear methods in the struggle against classical problems
title_sort new sublinear methods in the struggle against classical problems
topic Electrical Engineering and Computer Science.
url http://hdl.handle.net/1721.1/62428
work_keys_str_mv AT onakkrzysztofkrzysztofpiotr newsublinearmethodsinthestruggleagainstclassicalproblems