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We study the problem of navigating through a database of similar objects using comparisons. This problem is known to be strongly related to the small-world network design problem.
We consider a basic problem in unsupervised learning: learning an unknown \emph{Poisson Binomial Distribution} over $\{0,1,...,n\}$. A Poisson Binomial Distribution (PBD) is a sum $X = X_1 + ... + X_n...
In a recent paper, Bassett et al. (2011) have analyzed the static and dynamic organization of functional brain networks in humans.
Given the output of a data source taking values in a finite alphabet, we wish to detect change-points, that is times when the statistical properties of the source change.
We provide rigorous guarantees on learning with the weighted trace-norm under arbitrary sampling distributions.
This paper is devoted to the problem of sampling Gaussian fields in high dimension. Solutions exist for two specific structures of inverse covariance : sparse and circulant. The proposed approach is...
In order to compute the log-likelihood for high dimensional spatial Gaussian models, it is necessary to compute the determinant of the large, sparse, symmetric positive definite precision matrix, Q....
A new approach to adaptive design of clinical trials is proposed in a general multi- parameter exponential family setting, based on generalized likelihood ratio statistics and optimal sequential tes...
This paper considers the problem of adaptive estimation of a non-homogeneous intensity function from the observation of n independent Poisson processes having a common intensity that is randomly shi...
The delta method is a popular and elementary tool for deriving limiting distributions of transformed statistics, while applications of asymptotic distributions do not allow one to obtain desirable a...
In data sets with many more features than observations, independent screening based on all univariate regression models leads to a computationally convenient variable selection method. Recent effort...
We propose in this paper a random intercept Poisson model in which the random effect distribution is assumed to follow a generalized log-gamma (GLG) distribution. We derive the first two moments for...
We propose a new, nonparametric method for multivariate regression subject to convexity or concavity constraints on the response function. Convexity constraints are common in economics, statistics, ...
This paper deals with the nonparametric estimation in heteroscedastic regression Yi = f(Xi) + i; i = 1; : : : ; n, with incomplete information, i.e. each real random variable i has a density gi wh...
A self-contained Fortran-77 program for calculating test statistics to compare weighted histogram with an unweighted histogram and two histograms with weighted entries is presented. The code calcula...

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