A bstract We present a novel construction for Higgs-VEV sensitive (HVS) operator, which can be used as trigger operator in cosmic selection models the electroweak hierarchy problem. Our does not contain any degrees of freedom charged under SM gauge symmetries, leading to reduced tuning resulting models. is based on extension two Higgs doublet model (2HDM) with softly broken approximate global D...

An emerging way of tackling the dimensionality issues arising in the modeling of a multivariate process is to assume that the inherent data structure can be captured by a graph. Nevertheless, though state-of-the-art graph-based methods have been successful for many learning tasks, they do not consider time-evolving signals and thus are not suitable for prediction. Based on the recently introduc...

We study the properties of affine rigidity of a hypergraph and prove a variety of fundamental results. First, we show that affine rigidity is a generic property (i.e., depends only on the hypergraph, not the particular embedding). Then we prove that a graph is generically neighborhood affinely rigid in d-dimensional space if it is (d+1)-vertex-connected. We also show neighborhood affine rigidit...

<p style='text-indent:20px;'>Joint densities for a sequential pair of returns with weak autocorrelation and strong correlation in squared are formulated. The marginal return either variance gamma or bilateral gamma. Two-dimensional matching empirical characteristic functions to its theoretical counterpart is employed dependency parameter estimation. Estimations reported 3920 daily sequenc...

Squared planar markers are a popular tool for fast, accurate and robust camera localization, but its use is frequently limited to a single marker, or at most, to a small set of them for which their relative pose is known beforehand. Mapping and localization from a large set of planar markers is yet a scarcely treated problem in favour of keypoint-based approaches. However, while keypoint detect...

A new method for model selection for Gaussian Bayesian networks and Markov networks, with extensions towards ancestral graphs, is constructed to have good mean squared error properties. The method is based on the focused information criterion, and offers the possibility of fitting individualtailored models. The focus of the research, that is, the purpose of the model, directs the selection. It ...

Various subspace clustering methods have benefited from introducing a graph regularisation term in their objective functions. In this work, we identify two critical limitations of the graph regularisation term employed in existing subspace clustering models and provide solutions for both of them. First, the squared l2-norm used in the existing term is replaced by a l1-norm term to make the regu...