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HACKING SPATIAL DATA: AN EXAMPLE OF AGGREGATION PROBLEMS
Spatial aggregation Spatial data science Hacking spatial data Spatial autocorrelation
2018/11/8
Many applications using spatially aggregated data tend to treat the spatial units as given. For example, in the United States, analyses using the social and economic data often rely on the existing an...
Recent years have seen an increasing interest in the use of panoramic models to document architectural and archeological sites. A stereo-panorama is a new extension to a panoramic model which improves...
Successive pattern learning based on test feature classifier and its application to dynamic recognition problems
classifi cation test feature classifi er successive learning dynamic recognition problem
2015/8/25
Fundamental characteristics of successive lerarning by Test Feature Classifier(TFC), which is non-parametric and effective with small data, are examined. In the learning, a new set of training o...
Recovering Edges in Ill-Posed Inverse Problems:Optimality of Curvelet Frames
Ill-Posed Inverse Problems Regularization Singular Value Decomposition Radon Transform Deconvolution Edge Edge-Preserving Regularization Wavelets Curvelets Ridgelets Wavelet-Vaguelette-Decomposition Wavelet Shrinkage Minimax Estimation Optimal Rates of Convergence White Noise Model
2015/6/17
We consider a model problem of recovering a function f(x1, x2) from noisy Radon data. The function f to be recovered is assumed smooth apart from a discontinuity along a C2 curve – i.e. an edge. We us...
Templates for Convex Cone Problems with Applications to Sparse Signal Recovery
Optimal first-order methods Nesterov’s accelerated descent algorithms proximal algorithms conic duality smoothing by conjugation the Dantzig selector the LASSO nuclearnorm minimization
2015/6/17
This paper develops a general framework for solving a variety of convex cone problems that frequently arise in signal processing, machine learning, statistics, and other fields. The approach works as ...