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ICC
2007
IEEE
142views Communications» more  ICC 2007»
15 years 4 months ago
Reduced-Complexity Cluster Modelling for the 3GPP Channel Model
—The realistic performance of a multi-input multi-output (MIMO) communication system depends strongly on the spatial correlation properties introduced by clustering in the propag...
Hui Xiao, Alister G. Burr, Rodrigo C. de Lamare
KDD
2005
ACM
166views Data Mining» more  KDD 2005»
15 years 10 months ago
A general model for clustering binary data
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Tao Li
ORDER
2008
82views more  ORDER 2008»
14 years 9 months ago
Profinite Heyting Algebras
For a Heyting algebra A, we show that the following conditions are equivalent: (i) A is profinite; (ii) A is finitely approximable, complete, and completely join-prime generated; (...
Guram Bezhanishvili, Nick Bezhanishvili
ICIP
2005
IEEE
15 years 11 months ago
Sampling schemes for 2-D signals with finite rate of innovation using kernels that reproduce polynomials
In this paper, we propose new sampling schemes for classes of 2-D signals with finite rate of innovation (FRI). In particular, we consider sets of 2-D Diracs and bilevel polygons....
Pancham Shukla, Pier Luigi Dragotti
ICML
2005
IEEE
15 years 10 months ago
Predictive low-rank decomposition for kernel methods
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
Francis R. Bach, Michael I. Jordan