Results 1 to 10 of about 1,884,911 (319)
Near-medians that avoid the corners; a combinatorial probability approach. [PDF]
BMC Genomics, 2014 The breakpoint median for a set of k ≥ 3 random genomes tends to approach (any) one of these genomes ("corners") as genome length increases, although there are diminishing proportion of medians equidistant from all k ("medians in the middle"). Algorithms are likely to miss the latter, and this has consequences for the general case where input genomes ...
Larlee C, Zheng C, Sankoff D.
europepmc +7 more sources
Probability-boosting technique for combinatorial optimization [PDF]
PeerJ Computer ScienceIn many combinatorial optimization problems we want a particular set of k out of n items with some certain properties (or constraints). These properties may involve the k items.
Sanpawat Kantabutra
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Possibilities determine the combinatorial structure of probability polytopes [PDF]
Journal of Mathematical Psychology, 2016 We study the set of no-signalling empirical models on a measurement scenario, and show that the combinatorial structure of the no-signalling polytope is completely determined by the possibilistic information given by the support of the models. This is a special case of a general result which applies to all polytopes presented in a standard form, given ...
Samson Abramsky +4 more
semanticscholar +8 more sources
Generating Functions for New Families of Combinatorial Numbers and Polynomials: Approach to Poisson–Charlier Polynomials and Probability Distribution Function [PDF]
Axioms, 2019 The aim of this paper is to construct generating functions for new families of combinatorial numbers and polynomials. By using these generating functions with their functional and differential equations, we not only investigate properties of these new ...
Irem Kucukoglu +2 more
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A combinatorial lemma and its application to probability theory [PDF]
Transactions of the American Mathematical Society, 1956 To explain the idea behind the present paper the following fundamental principle is emphasized. Let X = (X 1,…, X n ) be an n-dimensional vector valued random variable, and let µ(x) =µ(x 1…, x n )be its probability measure (defined on euclidean n-space E n ).
Frank Spitzer
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Probability and Problems in Euclidean Combinatorial Optimization [PDF]
Statistical Science, 1993 This article summarizes the current status of several streams of research that deal with the probability theory of problems of combina- torial optimization. There is a particular emphasis on functionals of finite point sets. The most famous example of such functionals is the length associated with the Euclidean traveling salesman problem (TSP), but ...
John Steele
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Extremal Probability Bounds in Combinatorial Optimization [PDF]
SIAM Journal on Optimization, 2021 In this paper, we compute the tightest possible bounds on the probability that the optimal value of a combinatorial optimization problem in maximization form with a random objective exceeds a given number, assuming only knowledge of the marginal distributions of the objective coefficient vector.
Divya Padmanabhan +3 more
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Scientific Creativity: Discovery and Invention as Combinatorial
Frontiers in Psychology, 2021 Although scientific creativity has often been described as combinatorial, the description is usually insufficiently formulated to count as a precise scientific explanation.
Dean Keith Simonton
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BMC Bioinformatics, 2021 Background Systems biology increasingly relies on deep sequencing with combinatorial index tags to associate biological sequences with their sample, cell, or molecule of origin.
Lior Galanti +2 more
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Combinatorial probability and the tightness of generalization bounds [PDF]
Pattern Recognition and Image Analysis, 2008 Accurate prediction of the generalization ability of a learning algorithm is an important problem in computational learning theory. The classical Vapnik-Chervonenkis (VC) generalization bounds are too general and therefore overestimate the expected error. Recently obtained data-dependent bounds are still overestimated.
Konstantin Vorontsov
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