Results 1  10
of
97
XIRQL: A Query Language for Information Retrieval in XML Documents
, 2001
"... Based on the documentcentric view of XML, we present the query language XIRQL. Current proposals for XML query languages lack most IRrelated features, which are weighting and ranking, relevanceoriented search, datatypes with vague predicates, and semantic relativism. XIRQL integrates these featur ..."
Abstract

Cited by 188 (6 self)
 Add to MetaCart
Based on the documentcentric view of XML, we present the query language XIRQL. Current proposals for XML query languages lack most IRrelated features, which are weighting and ranking, relevanceoriented search, datatypes with vague predicates, and semantic relativism. XIRQL integrates these features by using ideas from logicbased probabilistic IR models, in combination with concepts from the database area. For processing XIRQL queries, a path algebra is presented, that also serves as a starting point for query optimization.
On Advances in Statistical Modeling of Natural Images
, 2003
"... Statistical analysis of images reveals two interesting properties: (i) invariance of image statistics to scaling of images, and (ii) nonGaussian behavior of image statistics, i.e. high kurtosis, heavy tails, and sharp central cusps. In this paper we review some recent results in statistical modeli ..."
Abstract

Cited by 145 (7 self)
 Add to MetaCart
Statistical analysis of images reveals two interesting properties: (i) invariance of image statistics to scaling of images, and (ii) nonGaussian behavior of image statistics, i.e. high kurtosis, heavy tails, and sharp central cusps. In this paper we review some recent results in statistical modeling of natural images that attempt to explain these patterns. Two categories of results are considered: (i) studies of probability models of images or image decompositions (such as Fourier or wavelet decompositions), and (ii) discoveries of underlying image manifolds while restricting to natural images. Applications of these models in areas such as texture analysis, image classification, compression, and denoising are also considered.
THE MARKOV CHAIN MONTE CARLO REVOLUTION
"... Abstract. The use of simulation for highdimensional intractable computations has revolutionized applied mathematics. Designing, improving and understanding the new tools leads to (and leans on) fascinating mathematics, from representation theory through microlocal analysis. 1. ..."
Abstract

Cited by 46 (0 self)
 Add to MetaCart
(Show Context)
Abstract. The use of simulation for highdimensional intractable computations has revolutionized applied mathematics. Designing, improving and understanding the new tools leads to (and leans on) fascinating mathematics, from representation theory through microlocal analysis. 1.
A GUE central limit theorem and universality of directed first and last passage site percolation
 Int. Math. Res. Not
, 2005
"... Abstract. We prove a GUE central limit theorem for random variables with finite fourth moment. We apply this theorem to prove that the directed first and last passage percolation problems in thin rectangles exhibit universal fluctuations given by the TracyWidom law. In addition, we conjecture a pre ..."
Abstract

Cited by 27 (3 self)
 Add to MetaCart
(Show Context)
Abstract. We prove a GUE central limit theorem for random variables with finite fourth moment. We apply this theorem to prove that the directed first and last passage percolation problems in thin rectangles exhibit universal fluctuations given by the TracyWidom law. In addition, we conjecture a precise value for the time constant in the general first and last passage problems. 1.
A CLT for Informationtheoretic statistics of Gram random matrices with a given variance profile
, 2008
"... Consider a N × n random matrix Yn = (Y n ij) where the entries are given by Y n σij(n) ij = √ X n n ij, the Xn ij being centered, independent and identically distributed random variables with unit variance and (σij(n); 1 ≤ i ≤ N,1 ≤ j ≤ n) being an array of numbers we shall refer to as a variance ..."
Abstract

Cited by 23 (7 self)
 Add to MetaCart
(Show Context)
Consider a N × n random matrix Yn = (Y n ij) where the entries are given by Y n σij(n) ij = √ X n n ij, the Xn ij being centered, independent and identically distributed random variables with unit variance and (σij(n); 1 ≤ i ≤ N,1 ≤ j ≤ n) being an array of numbers we shall refer to as a variance profile. We study in this article the fluctuations of the random variable log det (YnY ∗ n + ρIN) where Y ∗ is the Hermitian adjoint of Y and ρ> 0 is an additional parameter. We prove that when centered and properly rescaled, this random variable satisfies a Central Limit Theorem (CLT) and has a Gaussian limit whose parameters are identified. A complete description of the scaling parameter is given; in particular it is shown that an additional term appears in this parameter in the case where the 4 th moment of the Xij’s differs from the 4 th moment of a Gaussian random variable. Such a CLT is of interest in the field of wireless communications.
Flows, coalescence and noise
, 2002
"... We are interested in stationary "fluid" random evolutions with independent increments. Under some mild assumptions, we show they are solutions of a stochastic differential equation (SDE). There are situations where these evolutions are not described by flows of diffeomorphisms, but by coal ..."
Abstract

Cited by 21 (3 self)
 Add to MetaCart
(Show Context)
We are interested in stationary "fluid" random evolutions with independent increments. Under some mild assumptions, we show they are solutions of a stochastic differential equation (SDE). There are situations where these evolutions are not described by flows of diffeomorphisms, but by coalescing flows or by flows of probability kernels. In an intermediate phase, for which there exists a coalescing flow and a flow of kernels solution of the SDE, a classification is given: All solutions of the SDE can be obtained by filtering a coalescing motion with respect to a subnoise containing the Gaussian part of its noise. Thus, the coalescing motion cannot be described by a white noise.
The Skorokhod embedding problem and its offspring
, 2004
"... This is a survey about the Skorokhod embedding problem. It presents all known solutions together with their properties and some applications. Some of the solutions are just described, while others are studied in detail and their proofs are presented. A certain unification of proofs, based on onedi ..."
Abstract

Cited by 13 (2 self)
 Add to MetaCart
This is a survey about the Skorokhod embedding problem. It presents all known solutions together with their properties and some applications. Some of the solutions are just described, while others are studied in detail and their proofs are presented. A certain unification of proofs, based on onedimensional potential theory, is made. Some new facts which appeared in a natural way when different solutions were crossexamined, are reported. Azéma and Yor’s and Root’s solutions are studied extensively. A possible use of the latter is suggested together with a conjecture.
Gumbel fluctuations for cover times in the discrete torus. Probab. Theory Related Fields
, 2013
"... ar ..."
(Show Context)
Bayesian Computational Approaches to Model Selection
, 2000
"... this paper was to provide a summary of the stateof theart theory on Bayesian model selection and the application of MCMC algorithms. It has been shown how applications of considerable complexity can be handled successfully within this framework. Several methods for dealing with the use of default, ..."
Abstract

Cited by 9 (1 self)
 Add to MetaCart
this paper was to provide a summary of the stateof theart theory on Bayesian model selection and the application of MCMC algorithms. It has been shown how applications of considerable complexity can be handled successfully within this framework. Several methods for dealing with the use of default, improper priors in the Bayesian model selection 506 Andrieu, Doucet et al. framework has been shown. Special care has been taken to pinpoint the subtleties of jumping from one parameter space to another, and in general, to show the construction of MCMC samplers in such scenarios. The focus in the paper was on the reversible jump MCMC algorithm as this is the most widely used of all existing methods; it is easy to use, flexible and has nice properties. Many references have been cited, with the emphasis being given to articles with signal processing applications. A Notation
2008): “Identification and Nonparametric Estimation of a Transformed Additively Separable Model,” mimeo
"... [First Draft] Let r (x, z) be a function that can be identified nonparametrically. This paper discuss identification and consistent estimation of the unknown functions H, M, G and F, where r (x, z) = H [M (x, z)] and M (x, z) = G (x) + F (z). When r (x, z) represents a conditional mean function, t ..."
Abstract

Cited by 8 (3 self)
 Add to MetaCart
[First Draft] Let r (x, z) be a function that can be identified nonparametrically. This paper discuss identification and consistent estimation of the unknown functions H, M, G and F, where r (x, z) = H [M (x, z)] and M (x, z) = G (x) + F (z). When r (x, z) represents a conditional mean function, the centered, normalized estimators of the model’s unknown functions use marginal integration and are shown to have a limiting Normal distribution with a faster rate of convergence with respect to a fully unrestricted nonparametric regression. The small sample performance of the proposed estimators is studied in a small Monte Carlo experiment. We then implement our proposed procedure in order to nonparametrically identify, estimate and test generalized homothetic specifications for production functions in four different industries in the Chinese economy for two time periods.