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501
Measures on Tribes of Fuzzy Sets and the Role of Frank tnorms
"... As a natural generalization of a probability space, Butnariu and Klement introduced T tribes of fuzzy sets with probability T  measures. Their complete characterization was found for the case when T is a Frank tnorm. Here we characterize T measures with respect to nonFrank strict tnorms. We sh ..."
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As a natural generalization of a probability space, Butnariu and Klement introduced T tribes of fuzzy sets with probability T  measures. Their complete characterization was found for the case when T is a Frank tnorm. Here we characterize T measures with respect to nonFrank strict tnorms. We
Searching Remote Homology with Spectral Clustering with Symmetry in Neighborhood Cluster Kernels
, 2013
"... Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recogn ..."
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Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family
WebScale Information Extraction in KnowItAll
, 2004
"... Manually querying search engines in order to accumulate a large body of factual information is a tedious, errorprone process of piecemeal search. Search engines retrieve and rank potentially relevant documents for human perusal, but do not extract facts, assess confidence, or fuse information from ..."
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Cited by 96 (6 self)
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Manually querying search engines in order to accumulate a large body of factual information is a tedious, errorprone process of piecemeal search. Search engines retrieve and rank potentially relevant documents for human perusal, but do not extract facts, assess confidence, or fuse information from multiple documents. This paper introduces KNOWITALL, a system that aims to automate the tedious process of extracting large collections of facts from the web in an autonomous, domainindependent, and scalable manner.
Probabilistic and fractal aspects of Lévy trees
 Probab. Th. Rel. Fields
, 2005
"... We investigate the random continuous trees called Lévy trees, which are obtained as scaling limits of discrete GaltonWatson trees. We give a mathematically precise definition of these random trees as random variables taking values in the set of equivalence classes of compact rooted Rtrees, which i ..."
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Cited by 92 (21 self)
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We investigate the random continuous trees called Lévy trees, which are obtained as scaling limits of discrete GaltonWatson trees. We give a mathematically precise definition of these random trees as random variables taking values in the set of equivalence classes of compact rooted Rtrees, which is equipped with the GromovHausdorff distance. To construct Lévy trees, we make use of the coding by the height process which was studied in detail in previous work. We then investigate various probabilistic properties of Lévy trees. In particular we establish a branching property analogous to the wellknown property for GaltonWatson trees: Conditionally given the tree below level a, the subtrees originating from that level are distributed as the atoms of a Poisson point measure whose intensity involves a local time measure supported on the vertices at distance a from the root. We study regularity properties of local times in the space variable, and prove that the support of local time is the full level set, except for certain exceptional values of a corresponding to local extinctions. We also compute several fractal dimensions of Lévy trees, including Hausdorff and packing dimensions, in terms of lower and upper indices for the branching
Query expansion using random walk models
 In CIKM
, 2005
"... It has long been recognized that capturing term relationships is an important aspect of information retrieval. Even with large amounts of data, we usually only have significant evidence for a fraction of all potential term pairs. It is therefore important to consider whether multiple sources of evid ..."
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Cited by 73 (6 self)
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of evidence may be combined to predict term relations more accurately. This is particularly important when trying to predict the probability of relevance of a set of terms given a query, which may involve both lexical and semantic relations between the terms. We describe a Markov chain framework that combines
Particle swarm optimization  An Overview
 SWARM INTELL
, 2007
"... Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. As researchers have learned about the technique, they have derived new versions, developed new applications, and published theoretical studies of the effects of the various parameters and aspects of the algo ..."
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Cited by 82 (0 self)
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Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. As researchers have learned about the technique, they have derived new versions, developed new applications, and published theoretical studies of the effects of the various parameters and aspects of the algorithm. This paper comprises a snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems.
C: Comparative quantification of health risks: Global and regional burden of disease due to selected major risk factors. Geneva: World Health Organization
"... Comparative quantification of health risks: global and regional burden of disease attributable to selected major risk factors / edited by Majid Ezzati... [et al.]. 2 v. + v.3 in 1 CDROM. Contents: vol. 1, Childhood and maternal undernutrition—Other nutritionrelated risk factors and physical activi ..."
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Cited by 74 (1 self)
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Comparative quantification of health risks: global and regional burden of disease attributable to selected major risk factors / edited by Majid Ezzati... [et al.]. 2 v. + v.3 in 1 CDROM. Contents: vol. 1, Childhood and maternal undernutrition—Other nutritionrelated risk factors and physical activity—Addictive substances— vol. 2, Sexual and reproductive health—Environmental and occupational risks—Other selected risks—Distribution of risks by poverty—Data analysis and results—Multirisk assessment.—Annex tables CDROM, Population
Markov branching diffusions: martingales, Girsanov type theorems and applications to the long term behaviour
, 2001
"... Consider a spatial branching particle process where the underlying motion is a conservative diffusion on D ` R d corresponding to the elliptic operator L on D, and the branching is strictly binary (dyadic), with spatially varying rate fi(x) 0 (and fi 6j 0) which is assumed to be bounded from abo ..."
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Cited by 4 (3 self)
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Consider a spatial branching particle process where the underlying motion is a conservative diffusion on D ` R d corresponding to the elliptic operator L on D, and the branching is strictly binary (dyadic), with spatially varying rate fi(x) 0 (and fi 6j 0) which is assumed to be bounded from above. We prove that, under extremely mild circumstances the process exhibits local extinction if and only if c 0, where c denotes the generalized principal eigenvalue for the operator L + fi on D. (This criterion is analogous to the one obtained by Pinsky (1996) for the local extinction of superdiffusions). Furthermore we show that when the process does not exhibit local extinction, every nonempty open subset is occupied infinitely often with positive probability which can be characterized by a solution bounded in (0; 1] to the semilinear elliptic equation Lu + fi(u 2 \Gamma u) = 0 on D. Moreover, in this case, there is an exponential rate of growth on sufficiently large compact domains, and this rate can be arbitrarily close to c . In order to reach these conclusions we first develop some results concerning innerproduct and multiplicative martingales and their relation to the operators L + fi and L + fi/ respectively, where / (x) = x 2 \Gamma x.
homology
, 2012
"... Spectral clustering on neighborhood kernels with modified symmetry for remote ..."
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Spectral clustering on neighborhood kernels with modified symmetry for remote
Sample path properties of anisotropic Gaussian random fields
, 2008
"... Anisotropic Gaussian random fields arise in probability theory and in various applications. Typical examples are fractional Brownian sheets, operatorscaling Gaussian fields with stationary increments, and the solution to the stochastic heat equation. This paper is concerned with sample path propert ..."
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Cited by 45 (16 self)
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Anisotropic Gaussian random fields arise in probability theory and in various applications. Typical examples are fractional Brownian sheets, operatorscaling Gaussian fields with stationary increments, and the solution to the stochastic heat equation. This paper is concerned with sample path properties of anisotropic Gaussian random fields in general. Let X = {X(t), t ∈ RN} be a Gaussian random field with values in Rd and with parameters H1,..., HN. Our goal is to characterize the anisotropic nature of X in terms of its parameters explicitly. Under some general conditions, we establish results on the modulus of continuity, small ball probabilities, fractal dimensions, hitting probabilities and local times of anisotropic Gaussian random fields. An important tool for our study is the various forms of strong local nondeterminism.
Results 1  10
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501