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MCS
2008
Springer
15 years 5 months ago
Dynamical low-rank approximation: applications and numerical experiments
Dynamical low-rank approximation is a differential-equation based approach to efficiently computing low-rank approximations to time-dependent large data matrices or to solutions o...
Achim Nonnenmacher, Christian Lubich
SIAMMAX
2010
134views more  SIAMMAX 2010»
15 years 28 days ago
Dynamical Tensor Approximation
For the approximation of time-dependent data tensors and of solutions to tensor differential equations by tensors of low Tucker rank, we study a computational approach that can be ...
Othmar Koch, Christian Lubich
ICDE
2003
IEEE
96views Database» more  ICDE 2003»
16 years 7 months ago
Pushing Aggregate Constraints by Divide-and-Approximate
Iceberg-cube mining is to compute the GROUP BY partitions, for all GROUP BY dimension lists, that satisfy a given aggregate constraint. Previous works have pushed anti-monotone co...
Ke Wang, Yuelong Jiang, Jeffrey Xu Yu, Guozhu Dong...
GECCO
2007
Springer
139views Optimization» more  GECCO 2007»
16 years 10 days ago
The role of speciation in spatial coevolutionary function approximation
The role of space is more and more accepted as a way to dramatically improve the success of coevolutionary function approximation. The process behind this success however is not y...
Folkert de Boer, Paulien Hogeweg
CP
2004
Springer
15 years 11 months ago
Quality of LP-Based Approximations for Highly Combinatorial Problems
We study the quality of LP-based approximation methods for pure combinatorial problems. We found that the quality of the LPrelaxation is a direct function of the underlying constra...
Lucian Leahu, Carla P. Gomes