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Smoothed Complexity Theory

Published: 11 May 2015 Publication History

Abstract

Smoothed analysis is a new way of analyzing algorithms introduced by Spielman and Teng. Classical methods like worst-case or average-case analysis have accompanying complexity classes, such as P and Avg-P, respectively. Whereas worst-case or average-case analysis give us a means to talk about the running time of a particular algorithm, complexity classes allow us to talk about the inherent difficulty of problems.
Smoothed analysis is a hybrid of worst-case and average-case analysis and compensates some of their drawbacks. Despite its success for the analysis of single algorithms and problems, there is no embedding of smoothed analysis into computational complexity theory, which is necessary to classify problems according to their intrinsic difficulty.
We propose a framework for smoothed complexity theory, define the relevant classes, and prove some first hardness results (of bounded halting and tiling) and tractability results (binary optimization problems, graph coloring, satisfiability) within this framework.

References

[1]
Sanjeev Arora and Boaz Barak. 2009. Computational Complexity: A Modern Approach. Cambridge University Press, New York, NY.
[2]
David Arthur, Bodo Manthey, and Heiko Röglin. 2011. Smoothed analysis of the k-means method. Journal of the ACM 58, 5, Article No. 19.
[3]
Cyril Banderier, René Beier, and Kurt Mehlhorn. 2003. Smoothed analysis of three combinatorial problems. In Mathematical Foundations of Computer Science 2003. Lecture Notes in Computer Science, Vol. 2747. Springer, 198--207.
[4]
René Beier and Berthold Vöcking. 2004. Random knapsack in expected polynomial time. Journal of Computer and System Sciences 69, 3, 306--329.
[5]
René Beier and Berthold Vöcking. 2006. Typical properties of winners and losers in discrete optimization. SIAM Journal on Computing 35, 4, 855--881.
[6]
Shai Ben-David, Benny Chor, Oded Goldreich, and Michael Luby. 1992. On the theory of average case complexity. Journal of Computer and System Sciences 44, 2, 193--219.
[7]
Markus Bläser, Bodo Manthey, and B. V. Raghavendra Rao. 2013. Smoothed analysis of partitioning algorithms for Euclidean functionals. Algorithmica 66, 2, 397--418.
[8]
Avrim L. Blum and John D. Dunagan. 2002. Smoothed analysis of the perceptron algorithm for linear programming. In Proceedings of the 13th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’02). 905--914.
[9]
Avrim L. Blum and Joel Spencer. 1995. Coloring random and semi-random k-colorable graphs. Journal of Algorithms 19, 2, 204--234.
[10]
Andrej Bogdanov and Luca Trevisan. 2006. Average-case complexity. Foundations and Trends in Theoretical Computer Science 2, 1, 1--106.
[11]
Tom Bohman, Alan M. Frieze, Michael Krivelevich, and Ryan Martin. 2004. Adding random edges to dense graphs. Random Structures and Algorithms 24, 2, 105--117.
[12]
Tobias Brunsch, Kamiel Cornelissen, Bodo Manthey, and Heiko Röglin. 2013a. Smoothed analysis of belief propagation for minimum-cost flow and matching. Journal of Graph Algorithms and Applications 17, 6, 647--670.
[13]
Tobias Brunsch, Kamiel Cornelissen, Bodo Manthey, and Heiko Röglin. 2013b. Smoothed analysis of the successive shortest path algorithm. In Proceedings of the 24th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’13). 1180--1189.
[14]
Tobias Brunsch and Heiko Röglin. 2015. Improved smoothed analysis of multiobjective optimization. Journal of the ACM 62, 1, 4.
[15]
Xi Chen, Xiaotie Deng, and Shang-Hua Teng. 2009. Settling the complexity of computing two-player Nash equilibria. Journal of the ACM 56, 3, Article No. 14.
[16]
Amin Coja-Oghlan. 2007a. Colouring semirandom graphs. Combinatorics, Probability and Computing 16, 4, 515--552.
[17]
Amin Coja-Oghlan. 2007b. Solving NP-hard semirandom graph problems in polynomial expected time. Journal of Algorithms 62, 1, 19--46.
[18]
Amin Coja-Oghlan, Uriel Feige, Alan M. Frieze, Michael Krivelevich, and Dan Vilenchik. 2009. On smoothed k-CNF formulas and the walksat algorithm. In Proceedings of the 20th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’09). 451--460.
[19]
Valentina Damerow, Bodo Manthey, Friedhelm Meyer auf der Heide, Harald Räcke, Christian Scheideler, Christian Sohler, and Till Tantau. 2012. Smoothed analysis of left-to-right maxima with applications. ACM Transactions on Algorithms 8, 3, Article No. 30.
[20]
Matthias Englert, Heiko Röglin, and Berthold Vöcking. 2014. Worst case and probabilistic analysis of the 2-opt algorithm for the TSP. Algorithmica 68, 1, 190--264.
[21]
Uriel Feige. 2007. Refuting smoothed 3CNF formulas. In Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS’07). IEEE, Los Alamitos, CA, 407--417.
[22]
Uriel Feige and Joe Kilian. 2001. Heuristics for semirandom graph problems. Journal of Computer and System Sciences 63, 4, 639--671.
[23]
Mahmoud Fouz, Manfred Kufleitner, Bodo Manthey, and Nima Zeini Jahromi. 2012. On smoothed analysis of quicksort and Hoare’s find. Algorithmica 62, 3--4, 879--905.
[24]
Michael R. Garey and David S. Johnson. 1979. Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman and Company, New York, NY.
[25]
Yuri Gurevich. 1991. Average case completeness. Journal of Computer and System Sciences 42, 3, 346--398.
[26]
Russell Impagliazzo, Ramamohan Paturi, and Francis Zane. 2001. Which problems have strongly exponential complexity? Journal of Computer and System Sciences 63, 4, 512--530.
[27]
Michael Krivelevich, Benny Sudakov, and Prasad Tetali. 2006. On smoothed analysis in dense graphs and formulas. Random Structures and Algorithms 29, 2, 180--193.
[28]
Leonid A. Levin. 1986. Average case complete problems. SIAM Journal on Computing 15, 1, 285--286.
[29]
Ming Li and Paul M. B. Vitányi. 1992. Average case complexity under the universal distribution equals worst-case complexity. Information Processing Letters 42, 3, 145--149.
[30]
Ming Li and Paul M. B. Vitányi. 1993. An Introduction to Kolmogorov Complexity and Its Applications. Springer, New York, NY.
[31]
Bodo Manthey and Rüdiger Reischuk. 2007. Smoothed analysis of binary search trees. Theoretical Computer Science 378, 3, 292--315.
[32]
Bodo Manthey and Heiko Röglin. 2011. Smoothed analysis: Analysis of algorithms beyond worst case. Information Technology 53, 6, 280--286.
[33]
Bodo Manthey and Heiko Röglin. 2013. Worst-case and smoothed analysis of k-means clustering with Bregman divergences. Journal of Computational Geometry 4, 1, 94--132.
[34]
Bodo Manthey and Rianne Veenstra. 2013. Smoothed analysis of the 2-opt heuristic for the TSP: Polynomial bounds for Gaussian noise. In Algorithms and Computation. Lecture Notes in Computer Science, Vol. 8283. Springer, 579--589.
[35]
Ankur Moitra and Ryan O’Donnell. 2011. Pareto optimal solutions for smoothed analysts. In Proceedings of the 43rd Annual ACM Symposium on Theory of Computing (STOC’11). ACM, New York, NY, 225--234.
[36]
Heiko Röglin and Shang-Hua Teng. 2009. Smoothed analysis of multiobjective optimization. In Proceedings of the 50th Annual IEEE Symposium on Foundations of Computer Science (FOCS’09). IEEE, Los Alamitos, CA, 681--690.
[37]
Heiko Röglin and Berthold Vöcking. 2007. Smoothed analysis of integer programming. Mathematical Programming 110, 1, 21--56.
[38]
Daniel A. Spielman and Shang-Hua Teng. 2003. Smoothed analysis of termination of linear programming algorithms. Mathematical Programming 97, 1--2, 375--404.
[39]
Daniel A. Spielman and Shang-Hua Teng. 2004. Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time. Journal of the ACM 51, 3, 385--463.
[40]
Daniel A. Spielman and Shang-Hua Teng. 2009. Smoothed analysis: An attempt to explain the behavior of algorithms in practice. Communications of the ACM 52, 10, 76--84.
[41]
Roman Vershynin. 2009. Beyond Hirsch conjecture: Walks on random polytopes and smoothed complexity of the simplex method. SIAM Journal on Computing 39, 2, 646--678.
[42]
Jie Wang. 1997. Average-case intractable NP problems. In Advances in Languages, Algorithms, and Complexity, D.-Z. Du and K.-I. Ko (Eds.). Kluwer, Dordrecht, Netherlands, 313--378.
[43]
Herbert S. Wilf. 1985. Some examples of combinatorial averaging. American Mathematical Monthly 92, 4, 250--261.

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cover image ACM Transactions on Computation Theory
ACM Transactions on Computation Theory  Volume 7, Issue 2
May 2015
101 pages
ISSN:1942-3454
EISSN:1942-3462
DOI:10.1145/2775140
Issue’s Table of Contents
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Association for Computing Machinery

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Publication History

Published: 11 May 2015
Accepted: 01 November 2014
Revised: 01 March 2014
Received: 01 March 2013
Published in TOCT Volume 7, Issue 2

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Author Tags

  1. Smoothed analysis
  2. average-case complexity
  3. computational complexity

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