A learning-based exploration approach is proposed to escape from the basins of attraction of converged-to optima, by selecting on what is termed the interestingness of a solution. This interestingness is based on the modeling error made by a surrogate model that is trained on all solutions encountered earlier during the search. Compared to multiple standard optimization runs, a learning-guided ...

Quantitative analysis of MR images is becoming increasingly important as a surrogate marker in clinical trials in multiple sclerosis (MS). This paper describes a fully automated model-based method for segmentation of MS lesions from multi-channel MR images. The method simultaneously corrects for MR eld inhomogeneities, estimates tissue class distribution parameters and classiies the image voxel...

Consider a set of 6 points in R × {0, 1}: {(−1, 1), (−1, 1), (−2, 1), (−3, 0), (−3, 0), (−3, 0)}, and suppose we are interested in Prec@1. Note that the optimum model that maximizes prec@1 on these points has a positive sign. We will now show that the model w∗ ∈ R that maximizes the above structural SVM surrogate on these points has a negative sign. On the contrary, let us assume that w∗ has a ...

Rokitansky syndrome is a developmental defect characterized by agenesis of the uterus and vagina but normal gonads and secondary sexual characters. It is not commonly transmitted as a dominant genetic trait. Surrogacy, which is legally and ethically accepted in the UK and other countries, has made it possible for the patients with this syndrome to have their own genetic children. Six patients w...

Fourier surrogate data are artificially generated time series, that — based on a resampling scheme — share the linear properties with an observed time series. In this paper we study a statistical surrogate hypothesis test to detect deviations from a linear Gaussian process with respect to asymmetry in time (Q-statistic). We apply this test to a Fourier representable function and obtain a repres...

This article describes model-based methods for global optimization. After introducing the global optimization framework, modeling approaches for stochastic algorithms are presented. We differentiate between models that use a distribution and models that use an explicit surrogate model. Fundamental aspects of and recent advances in surrogate-model based optimization are discussed. Strategies for...

Introduction: Indigenous Australians experience higher rates of renal disease and hypertension than non-Indigenous Australians. Low birth weight is recognized as a contributing factor in chronic disease and has been shown to increase the risk of renal failure in adulthood. A smaller kidney volume with fewer nephrons places an individual at risk of hypertension and renal failure. Indigenous Aust...

normal 0 false false false en-us x-none fa background : circulating endothelial cells (cecs) and e-selectin are known as sensitive and specific markers of endothelial dysfunction. this study investigated whether cecs and e-selectin are surrogate biomarkers of preeclampsia and if measurement of cecs and e-selectin, early in the third trimester, could be a means of predicting preeclampsia. method...

When carrying out design searches, traditional variable screening techniques can find it extremely difficult to distinguish between important and unimportant variables. This is particularly true when only a small number of simulations is combined with a parameterization which results in a large number of variables of seemingly equal importance. Here the authors present a variable reduction tech...