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We report characteristics of in-text citations in over five million full text articles from two large databases – the PubMed Central Open Access subset and Elsevier journals – as functions of time, textual progression, and scientific field. The purpose of ...
In this paper we study first passage percolation on a random graph model, the configuration model. We first introduce the notions of weighted diameter, which is the maximum of the weighted lengths of all optimal paths between any two vertices in the graph, ...
Mechanism design theory examines the design of allocation mechanisms or incentive systems involving multiple rational but self-interested agents and plays a central role in many societally important problems in economics. In mechanism design problems, agen ...
In this thesis, we focus on the problem of achieving practical privacy guarantees in machine learning (ML), where the classic differential privacy (DP) fails to maintain a good trade-off between user privacy and data utility. Differential privacy guarantee ...
We characterize the local smoothness and the asymptotic growth rate of the Levy white noise. We do so by characterizing the weighted Besov spaces in which it is located. We extend known results in two ways. First, we obtain new bounds for the local smoothn ...
Medical image segmentation is an important task forcomputer aided diagnosis. Pixelwise manual annotationsof large datasets require high expertise and is time consum-ing. Conventional data augmentations have limited benefitby not fully representing the unde ...
In this article we study imaginary Gaussian multiplicative chaos-namely a family of random generalized functions which can formally be written as e(iX(x)), where X is a log-correlated real-valued Gaussian field on R-d, that is, it has a logarithmic singula ...
The distribution of spatially aggregated data from a stochastic process may exhibit tail behaviour different from that of its marginal distributions. For a large class of aggregating functionals we introduce the -extremal coefficient, which quantifies this ...
Stochastic programming and distributionally robust optimization seek deterministic decisions that optimize a risk measure, possibly in view of the most adverse distribution in an ambiguity set. We investigate under which circumstances such deterministic de ...
We investigate a non-Markovian analogue of the Harris contact process in Z(d): an individual is attached to each site x is an element of Z(d), and it can be infected or healthy; the infection propagates to healthy neighbours just as in the usual contact pr ...