This paper proposes a hierarchical nonlinear approximation scheme for scalar-valued multivariate functions, where the main objective is to obtain an accurate approximation with using only very few function evaluations. To this end, our iterative method combines at any refinement step the selection of suitable evaluation points with kriging, a standard method for statistical data analysis. Parti...

A novel technique is presented to facilitate the implementation of hierarchical b-splines and their interfacing with conventional finite element implementations. The discrete interpretation of the two-scale relation, as common in subdivision schemes, is used to establish algebraic relations between the basis functions and their coefficients on different levels of the hierarchical b-spline basis...

The paper briefly describes a basic set of special combinatorial engineering frameworks for solving complex problems in the field of hierarchical modular systems. The frameworks consist of combinatorial problems (and corresponding models), which are interconnected/linked (e.g., by preference relation). Mainly, hierarchical morphological system model is used. The list of basic standard combinato...

A new color image segmentation method combining mean shift and hierarchical clustering algorithm is presented in this paper. The proposed algorithm preprocesses an input image by mean shift algorithm to form segmented regions that preserve the desirable discontinuity characteristics of image. The number of segmented regions, instead of the number of image pixels, is considered as the input data...

As the complexity of VLSI circuits increases, a hierarchical design approach becomes essential to shorten the design period 1]. Circuit clustering plays a fundamental role in hierarchical designs. Identifying strongly connected components in the netlist can signiicantly reduce the complexity of the circuit and improve the performance of the design process. A good clustering method should identi...

Shawki Areibi1 Anthony Vannelli 2 1 University of Waterloo, Canada [email protected] 2 University of Waterloo, Canada [email protected] ABSTRACT As the complexity of VLSI circuits increases, a hierarchical design approach becomes essential to shorten the design period [1]. Circuit clustering plays a fundamental role in hierarchical designs. Identifying strongly ...

To realize privacy data protection efficiently in hybrid cloud service, a hierarchical control architecture based multi-cluster MapReduce programming model (the Hierarchical MapReduce Model, HMR) is presented. Under this hierarchical control architecture, data isolation and placement among private cloud and public clouds according to the data privacy characteristic is implemented by the control...

Hierarchical clustering is a useful data-driven approach to classify complex data and has been used to analyze resting-state functional magnetic resonance imaging (fMRI) data and derive functional networks of the human brain at very large scale, such as the entire visual or sensory-motor cortex. In this study, we developed a voxel-wise, whole-brain hierarchical clustering framework to perform m...

Accurately translating genotype to phenotype requires accounting for the functional impact of genetic variation at many biological scales. Here we present a strategy for genotype-phenotype reasoning based on existing knowledge of cellular subsystems. These subsystems and their hierarchical organization are defined by the Gene Ontology or a complementary ontology inferred directly from previousl...

A well-designed loss function can effectively improve the characterization ability of network features without increasing amount calculation in model inference stage, and has become focus attention recent research. Given that existing lightweight adds a to last layer, which severely attenuates gradient during backpropagation process, we propose hierarchical polynomial kernel prototype this stud...