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Averagecase analysis for combinatorial problems
, 2006
"... This thesis considers the average case analysis of algorithms, focusing primarily on NPhard combinatorial optimization problems. It includes a catalog of distributions frequently used in averagecase analysis and a collection of mathematical tools that have been useful in studying these distributio ..."
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This thesis considers the average case analysis of algorithms, focusing primarily on NPhard combinatorial optimization problems. It includes a catalog of distributions frequently used in averagecase analysis and a collection of mathematical tools that have been useful in studying
Automatic AverageCase Analysis Of Algorithms
, 1990
"... Many probabilistic properties of elementary discrete combinatorial structures of interest for the averagecase analysis of algorithms prove to be decidable. This paper presents a general framework in which such decision procedures can be developed: It is based on a combination of generating functi ..."
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Cited by 66 (17 self)
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Many probabilistic properties of elementary discrete combinatorial structures of interest for the averagecase analysis of algorithms prove to be decidable. This paper presents a general framework in which such decision procedures can be developed: It is based on a combination of generating
AverageCase Analysis of Greedy Pursuit
"... Recent work on sparse approximation has focused on the theoretical performance of algorithms for random inputs. This averagecase behavior is typically far better than the behavior of the algorithm for the worst inputs. Moreover, an averagecase analysis fits naturally with the type of signals that ..."
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Recent work on sparse approximation has focused on the theoretical performance of algorithms for random inputs. This averagecase behavior is typically far better than the behavior of the algorithm for the worst inputs. Moreover, an averagecase analysis fits naturally with the type of signals
AverageCase Analysis of Multiuser Detectors
, 2001
"...  Based on correspondence between codedivision multipleaccess (CDMA) multiuser detection problem and statistical mechanics, I present a novel analytical result on the averagecase performance of CDMA multiuser detectors, in the largesystem limit and under some simplifying assumptions, using tools ..."
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Cited by 4 (0 self)
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 Based on correspondence between codedivision multipleaccess (CDMA) multiuser detection problem and statistical mechanics, I present a novel analytical result on the averagecase performance of CDMA multiuser detectors, in the largesystem limit and under some simplifying assumptions, using tools
AverageCase Analysis Using Kolmogorov Complexity
"... This expository paper demonstrates how to use Kolmogorov complexity to do the averagecase analysis via four examples, and exhibits a surprising property of the celebrated associated universal distribution. The four examples are: average case analysis of Heapsort [17, 15], average nnidistance betwe ..."
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This expository paper demonstrates how to use Kolmogorov complexity to do the averagecase analysis via four examples, and exhibits a surprising property of the celebrated associated universal distribution. The four examples are: average case analysis of Heapsort [17, 15], average nni
An Averagecase Analysis of Graph Search
"... Many problems in realworld applications require searching graphs. Understanding the performance of search algorithms has been one of the eminent tasks of heuristic search research. Despite the importance of graph search algorithms, the research of analyzing their performance is limited, and most wo ..."
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work on search algorithm analysis has been focused on tree search algorithms. One of the major obstacles to analyzing graph search is that no single graph is an appropriate representative of graph search problems. In this paper, we propose one possible approach to analyzing graph search: Analyzing
AverageCase Analysis of Algorithms and Data Structures
, 1990
"... This report is a contributed chapter to the Handbook of Theoretical Computer Science (NorthHolland, 1990). Its aim is to describe the main mathematical methods and applications in the averagecase analysis of algorithms and data structures. It comprises two parts: First, we present basic combinato ..."
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Cited by 105 (8 self)
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This report is a contributed chapter to the Handbook of Theoretical Computer Science (NorthHolland, 1990). Its aim is to describe the main mathematical methods and applications in the averagecase analysis of algorithms and data structures. It comprises two parts: First, we present basic
average case analysis
, 2011
"... Abstract. In this paper we investigate from a statistical point of view the expected compressionratiobetweenthesizeofaminimalDeterministicFiniteCoverAutomaton(DFCA) and the size of the minimal corresponding Determinitic Finite Automaton (DFA). Using sound statistical methods, we extend the experimen ..."
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Abstract. In this paper we investigate from a statistical point of view the expected compressionratiobetweenthesizeofaminimalDeterministicFiniteCoverAutomaton(DFCA) and the size of the minimal corresponding Determinitic Finite Automaton (DFA). Using sound statistical methods, we extend the experimental study done in [16], thus obtaining a much better picture of the compression power of DFCAs. We compute the expected ratio for the family of all finite languages, but also for various subfamilies of finite languages, such as prefix, suffixfree languages prefix and suffix closed languages, or (un)balanced languages. We also give an example of a family for which the expected compression ratio is very high. 1
Tractable AverageCase Analysis of Naive Bayesian Classifiers
"... In this paper we present an averagecase analysis of the naive Bayesian classifier, a simple induction algorithm that performs well in many domains. Our analysis assumes a monotone `M of N' target concept and training data that consists of independent Boolean attributes. The analysis supposes a ..."
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Cited by 9 (1 self)
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In this paper we present an averagecase analysis of the naive Bayesian classifier, a simple induction algorithm that performs well in many domains. Our analysis assumes a monotone `M of N' target concept and training data that consists of independent Boolean attributes. The analysis supposes
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