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Maximum likelihood from incomplete data via the EM algorithm
 JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B
, 1977
"... A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situat ..."
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Cited by 11972 (17 self)
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A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value
Progress in Computational Complexity Theory
"... We briefly survey a number of important recent achievements in Theoretical Computer Science (TCS), especially Computational Complexity Theory. We will discuss the PCP Theorem, its implications to inapproximability on combinatorial optimization problems; space bounded computations, especially dete ..."
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We briefly survey a number of important recent achievements in Theoretical Computer Science (TCS), especially Computational Complexity Theory. We will discuss the PCP Theorem, its implications to inapproximability on combinatorial optimization problems; space bounded computations, especially
Computational Complexity Theory
 Algorithms and Theory of Computation Handbook
, 1996
"... INTRODUCTION Computational complexity is the study of the resources, such as time and space (memory), required to solve computational problems. By quantifying these resources, complexity theory has profoundly affected our thinking about computation. Computability theory establishes the existence of ..."
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Cited by 3 (0 self)
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INTRODUCTION Computational complexity is the study of the resources, such as time and space (memory), required to solve computational problems. By quantifying these resources, complexity theory has profoundly affected our thinking about computation. Computability theory establishes the existence
COMPUTATIONAL COMPLEXITY THEORY
, 2008
"... Complexity theory is the part of theoretical computer science that attempts to prove that certain transformations from input to output are impossible to compute using a reasonable amount of resources. Theorem 1 below illustrates the type of ‘‘impossibility’ ’ proof that can sometimes be obtained (1) ..."
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Complexity theory is the part of theoretical computer science that attempts to prove that certain transformations from input to output are impossible to compute using a reasonable amount of resources. Theorem 1 below illustrates the type of ‘‘impossibility’ ’ proof that can sometimes be obtained (1
Generalized Quantifiers in Computational Complexity Theory
, 1998
"... A notion of generalized quantifier in computational complexity theory is developed and used to give a unified treatment of leaf language definability, oracle separations, type 2 operators, and circuits with monoidal gates. Relations to Lindstrom quantifiers are pointed out. 1 Introduction In this p ..."
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A notion of generalized quantifier in computational complexity theory is developed and used to give a unified treatment of leaf language definability, oracle separations, type 2 operators, and circuits with monoidal gates. Relations to Lindstrom quantifiers are pointed out. 1 Introduction
Averagecase computational complexity theory
 Complexity Theory Retrospective II
, 1997
"... ABSTRACT Being NPcomplete has been widely interpreted as being computationally intractable. But NPcompleteness is a worstcase concept. Some NPcomplete problems are \easy on average", but some may not be. How is one to know whether an NPcomplete problem is \di cult on average"? ..."
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Cited by 32 (2 self)
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"? The theory of averagecase computational complexity, initiated by Levin about ten years ago, is devoted to studying this problem. This paper is an attempt to provide an overview of the main ideas and results in this important new subarea of complexity theory. 1
A computational complexity theory in membrane computing
 In Păun et al
"... Summary. In this paper, a computational complexity theory within the framework of Membrane Computing is introduced. Polynomial complexity classes associated with different models of celllike and tissuelike membrane systems are defined and the most relevant results obtained so far are presented. Ma ..."
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Cited by 10 (7 self)
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Summary. In this paper, a computational complexity theory within the framework of Membrane Computing is introduced. Polynomial complexity classes associated with different models of celllike and tissuelike membrane systems are defined and the most relevant results obtained so far are presented
A generalized quantifier concept in computational complexity theory
, 1998
"... A notion of generalized quantifier in computational complexity theory is explored and used to give a unified treatment of leaf language definability, oracle separations, type 2 operators, and circuits with monoidal gates. Relations to Lindström quantifiers are pointed out. ..."
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Cited by 6 (2 self)
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A notion of generalized quantifier in computational complexity theory is explored and used to give a unified treatment of leaf language definability, oracle separations, type 2 operators, and circuits with monoidal gates. Relations to Lindström quantifiers are pointed out.
The Role of Parameterized Computational Complexity Theory in Cognitive Modeling
 In Ling, C.X. and Sun, R. (eds), Working Notes of AAAI96 Workshop on Computational Cognitive Modelling: Source of the Power. THE COMPUTER JOURNAL, 2007
, 1996
"... This paper shows how parameterized computational complexity theory is better than previouslyused theories of computational complexity, e.g., NPcompleteness, at both measuring the power of computational models of cognitive systems and isolating the sources of this power. This point is illustrated w ..."
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Cited by 5 (1 self)
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This paper shows how parameterized computational complexity theory is better than previouslyused theories of computational complexity, e.g., NPcompleteness, at both measuring the power of computational models of cognitive systems and isolating the sources of this power. This point is illustrated
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