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We consider a Kullback-Leibler-based algorithmfor the stochastic multi-armed bandit prob- lem in the case of distributions with finite supports (not necessarily known beforehand), whose asymptotic r...
We develop a coherent framework for integrative simultaneous analysis of the explorationexploitation and model order selection tradeoffs. We improve over our preceding results on the same subject ...
A methodology is proposed for inferring the topology underlying point cloud data. The approach employs basic elements of Morse Theory, and is capable of producing not only a point estimate of variou...
We present two alternative ways to apply PAC-Bayesian analysis to sequences of dependent random variables. The first is based on a new lemma that enables to bound expectations of convex functions of...
As McShane and Wyner (2011) observe, there are formidable statistical problems in “reconstructing” past temperatures from networks of so-called “proxy” data with weak “signaland complicated autoco...
This article (MW) has stimulated much valuable discussion and helped to focus attention on an important area for the application of statistics. Given the short amount of space, however, we reluctant...
Technology has had an unquestionable impact on the way people watch sports. As technology has evolved, so too has the knowledge of a casual sports fan. A direct result of this evolution is the amount ...
Understanding functional organization of genetic information is a major challenge in modern biology. Following the initial publication of the human genome sequence in 2001, advances in high-throughput...
We study regression models for the situation where both dependent and independent variables are square-integrable stochastic processes. Questions concerning the definition and existence of the corresp...
We propose a novel probabilistic method for detection of objects in noisy images. The method uses results from percolation and random graph theories. We present an algorithm that allows to detect obje...
While considerable advance has been made to account for statistical uncertainties in astronomical analyses, systematic instrumental uncertainties have been generally ignored. This can be crucial to a ...
Lasso and other regularization procedures are attractive methods for variable selection, subject to a proper choice of shrinkage parameter. Given a set of potential subsets produced by a regularizatio...
Causal mediation analysis is routinely conducted by applied researchers in a variety of disciplines. The goal of such an analysis is to investigate alternative causal mechanisms by examining the roles...
The paper proposes a latent variable model for binary data coming from an unobserved heterogeneous population. The heterogeneity is taken into account by replacing the traditional assumption of Gauss...
We present an applied study in cancer genomics for integrating data and inferences from laboratory experiments on cancer cell lines with observational data obtained from human breast cancer studies. T...

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