20 papers · ranked by Valyu relevance
Martin Brooks
Continuous interpolation of real-valued data is characterized by piecewise monotone functions on a compact metric space. Topological total variation of piecewise monotone function f : X → R is a homeomorphisminvariant generalization of 1D total variation. A varilet basis is an orthonormal collection of piecewise…
Huanyu Xu, Quansen Sun, Nan Luo, Guo Cao + 2 more
In this paper, a Bregman iteration based total variation image restoration algorithm is proposed. Based on the Bregman iteration, the algorithm splits the original total variation problem into sub-problems that are easy to solve. Moreover, non-local regularization is introduced into the proposed algorithm, and a method…
Weimin Han, Hengyong Yu, Ge Wang
Recently, in the compressed sensing framework we found that a two-dimensional interior region-of-interest (ROI) can be exactly reconstructed via the total variation minimization if the ROI is piecewise constant (Yu and Wang, 2009). Here we present a general theorem charactering a minimization property for a piecewise…
Clemens Kirisits, Eric Setterqvist
We prove that the $L^2$ distance between the minimizer of the $\ell ^1$-anisotropic Rudin-Osher-Fatemi (ROF) functional and its minimizer over the space of piecewise constant functions on a rectilinear grid is $\mathcal{O}h^{{1}/{2}-{q'}/{2q}}$, where h is the grid’s mesh size and the datum belongs to $L^q$, q \ge 2 q…
J. C. De los Reyes, C.-B. Schönlieb, T. Valkonen
We consider a bilevel optimisation approach for parameter learning in higher-order total variation image reconstruction models. Apart from the least squares cost functional, naturally used in bilevel learning, we propose and analyse an alternative cost based on a Huber-regularised TV seminorm. Differentiability…
Yan Zhang, Jiasong Wu, Youyong Kong, Gouenou Coatrieux + 2 more
'Huazhong Shu' 'Pew-Thian Yap'] Total variation (TV) based models are very popular in image denoising but suffer from some drawbacks. For example, local TV methods often cannot preserve edges and textures well when they face excessive smoothing. Non-local TV methods constitute an alternative, but their computational…
Joel P. Heath, Peter Borowski, Shu-Dong Zhang
Real quantities can undergo such a wide variety of dynamics that the mean is often a meaningless reference point for measuring variability. Despite their widespread application, techniques like the Coefficient of Variation are not truly proportional and exhibit pathological properties. The non-parametric measure…
Zoltán Botta-Dukát
Comparing within-species variations of traits can be used in testing ecological theories. In these comparisons, it is useful to remove the effect of the difference in mean trait values, therefore measures of relative variation, most often the coefficient of variation (CV), are used. The studied traits are often…
Mario Schlemmer
The variability in population abundances is of central concern for the quantification of evolutionary patterns and an indispensable tool for ecological analysis. Standard measures of population variability are often biased, insensitive to population crashes, and exhibit other pathological behavior. Here I introduce new…
Jian Yang, S. Hong Lee, Naomi R. Wray, Michael E. Goddard + 1 more
In a recent publication entitled “Limitations of GCTA as a solution to the missing heritability problem” Krishna Kumar et al. (2015 PNAS) claim that “GCTA applied to current SNP data cannot produce reliable or stable estimates of heritability”. Here we show that those claims are false and that results presented by…
Zhenghao Wu, Tianhang Zhou
In the realm of multiscale molecular simulations, structure-based coarse graining is a prominent approach for creating efficient coarse-grained (CG) representations of soft matter systems such as polymers. This involves optimizing CG interactions by matching static correlation functions of corresponding degrees of…
David Vanavermaete, Jan Fostier, Steven Maenhout, Bernard De Baets
Genomic selection has been successfully implemented in plant and animal breeding. The transition of parental selection based on phenotypic characteristics to genomic selection (GS) has reduced breeding time and cost while accelerating the rate of genetic progression. Although breeding methods have been adapted to…
Julien F. Ayroles, Sean M. Buchanan, Chelsea Jenney, Kyobi Skutt-Kakaria + 4 more
Variability is ubiquitous in nature and a fundamental feature of complex systems. Few studies, however, have investigated variance itself as a trait under genetic control. By focusing primarily on trait means and ignoring the effect of alternative alleles on trait variability, we may be missing an important axis of…
Yuting Su, Taizhong Hu, Zhenfeng Zou
The extreme cases of risk measures, when considered within the context of distributional ambiguity, provide significant guidance for practitioners specializing in risk management of quantitative finance and insurance. In contrast to the findings of preceding studies, we focus on the study of extreme-case risk measure…
Authors not listed
The GENERIC framework provides a robust structure for nonequilibrium dynamics but lacks a principled method to select reversible ($L$) and irreversible ($M$) brackets. Similarly, finite-time optimizations minimizing path-averaged reciprocal temperature exist but remain isolated. Here, we introduce the \textbf{Entropy…
Fabio Bellini, Tolulope Fadina, Ruodu Wang, Yunran Wei
From the mathematical point of view, our main result is a characterization of symmetric and comonotonic variability measures as mixtures of inter-Expected Shortfall differences, under a few additional technical conditions. Further, we study the stochastic orders induced by the pointwise comparison of inter-Expected…
Fabio Bellini, Muqiao Huang, Qiuqi Wang, Ruodu Wang
The Lambda Value-at-Risk (Λ-VaR) is a generalization of the Value-at-Risk (VaR), which has been actively studied in quantitative finance. Over the past two decades, the Expected Shortfall (ES) has become one of the most important risk measures alongside VaR because of its various desirable properties in the practice of…
Kristina Rognlien Dahl, Arne Bang Huseby
Classical environmental contours are used in structural design in order to obtain upper bounds on the failure probabilities of a large class of designs. Buffered environmental contours, first introduced in [4], serve the same purpose, but with respect to the so-called buffered failure probability. In contrast to…
Authors not listed
Optimizing the synthesis conditions of advanced materials is challenging, especially when outcomes are subject to inherent experimental uncertainties. Bayesian optimization is a popular tool for accelerating materials discovery, but its standard risk-neutral framework overlooks the variability of outcomes under…
Roba Bairakdar, Lu Cao, Mélina Mailhot
The concept of univariate Range Value-at-Risk, presented by Cont et al. (2010), is extended in the multidimensional setting. Traditional risk measures are not well suited when dealing with heavy-tail distributions and infinite tail expectations. The multivariate definitions of robust truncated tail expectations are…