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ICASSP
2011
IEEE
14 years 5 months ago
Co-clustering as multilinear decomposition with sparse latent factors
The K-means clustering problem seeks to partition the columns of a data matrix in subsets, such that columns in the same subset are ‘close’ to each other. The co-clustering pr...
Evangelos E. Papalexakis, Nicholas D. Sidiropoulos
DATAMINE
1999
140views more  DATAMINE 1999»
15 years 1 months ago
A Scalable Parallel Algorithm for Self-Organizing Maps with Applications to Sparse Data Mining Problems
Abstract. We describe a scalable parallel implementation of the self organizing map (SOM) suitable for datamining applications involving clustering or segmentation against large da...
Richard D. Lawrence, George S. Almasi, Holly E. Ru...
PARA
2004
Springer
15 years 7 months ago
Parallel Algorithms for Balanced Truncation Model Reduction of Sparse Systems
We describe the parallelization of an efficient algorithm for balanced truncation that allows to reduce models with state-space dimension up to O(105 ). The major computational tas...
José M. Badía, Peter Benner, Rafael ...
GIS
2008
ACM
15 years 3 months ago
Sparse terrain pyramids
Bintrees based on longest edge bisection and hierarchies of diamonds are popular multiresolution techniques on regularly sampled terrain datasets. In this work, we consider sparse...
Kenneth Weiss, Leila De Floriani
ISCIS
2003
Springer
15 years 7 months ago
Minimizing Communication Cost in Fine-Grain Partitioning of Sparse Matrices
Abstract. We show a two-phase approach for minimizing various communication-cost metrics in fine-grain partitioning of sparse matrices for parallel processing. In the first phase...
Bora Uçar, Cevdet Aykanat