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On a link between kernel mean maps and Fraunhofer diffraction, with an application to super-resolution beyond the diffraction limit
On a link between kernel mean maps Fraunhofer diffraction an application super-resolution beyond the diffraction limit
2013/4/28
We establish a link between Fourier optics and a recent construction from the machine learning community termed the kernel mean map. Using the Fraunhofer approximation, it identifies the kernel with t...
Efficient Estimators for Sequential and Resolution-Limited Inverse Problems
deconvolution ill-posed image processing sig-nal recovery
2012/9/18
A common problem in the sciences is that a signal of interest is observed only indirectly, through smooth functionals of the signal whose values are then obscured by noise. In suchinverse problems, th...
On Steinhaus' resolution of the St. Petersburg paradox
Steinhaus' resolution the St. Petersburg paradox
2009/9/23
We elaborate on an interesting idea of Hugo Steinhaus
from 1949 concerning the St. Petersburg paradox.
Multi-Scale and Hidden Resolution Time Series Models
Autoregressive models Bayesian inference Combination of multiresolution information Jerey rule of conditioning
2009/9/21
We introduce a class of multi-scale models for time series. The novel framework couples standard linear models at dierent levels of resolution via stochastic links across scales. Jerey rule of conditi...
Characterization of Balanced Fractional 2m Factorial Designs of Resolution R*({1}|3) and GA-optimal Designs
association algebra BFF designs estimable parametric functions GA-optimality criterion resolution simple arrays
2009/3/10
In this paper, based on the assumption that the four-factor and higher-order interactions are to be negligible, we consider a balanced fractional 2m factorial design derived from a simple array such t...