abstract scaling methods, which are based on similar media theory, are used to simplify the statistic description of soil spatial variations. to simulate the water flow in heterogeneous soils, simultaneous scaling of soil hydraulic functions, including soil water retention and unsaturated hydraulic conductivity functions, is highly desirable. in the similar media theory, the simultaneous scalin...

Simultaneous matrix diagonalization is a key subroutine in many machine learning problems, including blind source separation and parameter estimation in latent variable models. Here, we extend joint diagonalization algorithms to low-rank and asymmetric matrices and also provide extensions to the perturbation analysis of these methods. Our results allow joint diagonalization to scale to larger p...

This paper presents a new approach using simultaneous voltage-scaling and gate-sizing for low power without violating the timing constraints. We provide the problem formulation in this application, and propose algorithms for single voltagescaling, single gate-sizing, and their simultaneous manipulation. We target a globally optimal solution by showing how the power optimization is related to th...

Using different experimental techniques, we examine the dynamical scaling of the quantum Hall plateau transition in a frequency range f=0.1-55 GHz. We present a scheme that allows for a simultaneous scaling analysis of these experiments and all other data in literature. We observe a universal scaling function with an exponent kappa=0.5+/-0.1, yielding a dynamical exponent z=0.9+/-0.2.

Random fields are a useful tool for modelling spatial phenomenon like environmental fields, including for example, hydrology, geology, oceanography and medical images. Many times the chosen model has to include some statistical dependence structure that might be present across the scales. Thus, an usual assumption is self-similarity (see [Lamp62]), defined for a random field {X(x)}x∈Rd on R by