Computational Geometry in High-Dimensional Spaces

Nearest Neighbors in High-Dimensional Spaces

A Geometry Preserving Kernel over Riemannian Manifolds

Abstract- Kernel trick and projection to tangent spaces are two choices for linearizing the data points lying on Riemannian manifolds. These approaches are used to provide the prerequisites for applying standard machine learning methods on Riemannian manifolds. Classical kernels implicitly project data to high dimensional feature space without considering the intrinsic geometry of data points. ...

Numerical Study of the tongue geometry effects on the cavitation and performance of a centrifugal pump in off-design conditions

In this study, the effects of the volute tongue geometry variation on the head, efficiency, velocity distribution and cavitation structure of a centrifugal pump in the steady flow behavior under off-design conditions have been investigated. Numerical simulation modeling based on the  turbulence model with a hybrid grid is used to simulate the flow within the modeled pump. The flow is simulated ...

Scaling Up MAP-Elites Using Centroidal Voronoi Tessellations

The recently introduced Multi-dimensional Archive of Phenotypic Elites (MAP-Elites) is an evolutionary algorithm capable of producing a large archive of diverse, high-performing solutions in a single run. It works by discretizing a continuous feature space into unique regions according to the desired discretization per dimension. While simple, this algorithm has a main drawback: it cannot scale...

Computational simulations of nanoparticle transport in a three-dimensional capillary network

Objective(s): Multifunctional nanomedicine is the new generation of medicine, which is remarkably promising and associated with the minimum toxicity of targeted therapy. Distribution and transport of nanoparticles (NPs) in the blood flow are essential to the evaluation of delivery efficacy. Materials and Methods: In the present study, we initially designed a phantom based on Murray’s mini...