In this work, we study a visual data mining problem: Given a set of discovered overlapping submatrices of interest, how can we order the rows and columns of the data matrix to bes...
Ruoming Jin, Yang Xiang, David Fuhry, Feodor F. Dr...
Spatial co-location patterns represent the subsets of features whose instances are frequently located together in geographic space. Co-location pattern discovery presents challeng...
In this paper, we propose a novel method, called local nonnegative matrix factorization (LNMF), for learning spatially localized, parts-based subspace representation of visual pat...
Stan Z. Li, XinWen Hou, HongJiang Zhang, QianSheng...
We present an example of a joint spatial and temporal task learning algorithm that results in a generative model that has applications for on-line visual control. We review work o...
This paper describes a new technique to visualize 2D flow fields with a sparse collection of dots. A cognitive model proposed by Kent Stevens describes how spatially local con...
Laura Tateosian, Brent M. Dennis, Christopher G. H...