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Average-case complexity

About: Average-case complexity is a research topic. Over the lifetime, 1749 publications have been published within this topic receiving 44972 citations.


Papers
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Proceedings ArticleDOI
01 Nov 2012
TL;DR: Experimental comparison on time complexity of algorithm for creation of Generalized One-Sided Concept Lattices according to the sparseness of the input data table between standard and sparse-based implementation is provided.
Abstract: In this paper we provide experimental comparison on time complexity of algorithm for creation of Generalized One-Sided Concept Lattices according to the sparseness of the input data table between standard and sparse-based implementation. It is an incremental algorithm related to FCA (Formal Concept Analysis), which is ready to be used with various attribute types and to create so-called generalized one-sided concept lattice. While these algorithms are generally exponential, in practice the complexity can be considerably reduced, e.g., for sparse input data tables. We describe sparse-based implementation of two crucial operations in our algorithm and provide experiments with different sparse data tables, where time complexity is studied for comparison of standard and sparse-based implementation of the algorithm.

7 citations

Journal ArticleDOI
Ed Blakey1
TL;DR: It is argued that traditional complexity theory does not adequately capture the true complexity of certain non-Turing computers, and, hence, that an extension of the theory is needed in order to accommodate such machines.

7 citations

Proceedings ArticleDOI
01 May 2000
TL;DR: This paper defines several variants of metaquerying that encompass, as far as the authors know, all variants defined in the literature, and shows that, under the combined complexity measure, metaqueries is generally intractable (unless P=NP), but is able to single out some tractable interesting metaqueries.
Abstract: Metaquerying is a datamining technology by which hidden dependencies among several database relations can be discovered. This tool has already been successfully applied to several real-world applications. Recent papers provide only very preliminary results about the complexity of metaquerying. In this paper we define several variants of metaquerying that encompass, as far as we know, all variants defined in the literature. We study both the combined complexity and the data complexity of these variants. We show that, under the combined complexity measure, metaquerying is generally intractable (unless P=NP), but we are able to single out some tractable interesting metaquerying cases (whose combined complexity is LOGCFL-complete). As for the data complexity of metaquerying, we prove that, in general, this is in P, but lies within AC0 in some interesting cases. Finally, we discuss the issue of equivalence between metaqueries, which is useful for optimization purposes.

7 citations

Dissertation
01 Jan 1984

7 citations

Book ChapterDOI
13 Dec 2010
TL;DR: It is proved that any connected graph can be transformed into a synchronized one by making suitable groups of twin vertices and it is deduced that anyconnected graph is the induced subgraph of a synchronizing graph, implying a big structural complexity of synchronizability.
Abstract: This article deals with the general ideas of almost global synchronization of Kuramoto coupled oscillators and synchronizing graphs. It reviews the main existing results and gives some new results about the complexity of the problem. It is proved that any connected graph can be transformed into a synchronized one by making suitable groups of twin vertices. As a corollary it is deduced that any connected graph is the induced subgraph of a synchronizing graph. This implies a big structural complexity of synchronizability. Finally the former is applied to find a two integer parameter family G(a,b) of connected graphs such that if b is the k-th power of 10, the synchronizability of G(a,b) is equivalent to find the k-th digit in the expansion in base 10 of the square root of 2. Thus, the complexity of classify G(a,b) is of the same order than the computation of square root of 2. This is the first result so far about the computational complexity of the synchronizability problem.

7 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20222
20216
202010
20199
201810
201732