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» Algorithms for Large Integer Matrix Problems
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ISSAC
1997
Springer
105views Mathematics» more  ISSAC 1997»
13 years 11 months ago
On Randomized Lanczos Algorithms
Las Vegas algorithms that are based on Lanczos’s method for solving symmetric linear systems are presented and analyzed. These are compared to a similar randomized Lanczos algor...
Wayne Eberly, Erich Kaltofen
SIGMOD
2008
ACM
157views Database» more  SIGMOD 2008»
14 years 7 months ago
CRD: fast co-clustering on large datasets utilizing sampling-based matrix decomposition
The problem of simultaneously clustering columns and rows (coclustering) arises in important applications, such as text data mining, microarray analysis, and recommendation system...
Feng Pan, Xiang Zhang, Wei Wang 0010
COR
2010
177views more  COR 2010»
13 years 7 months ago
Hybridization of very large neighborhood search for ready-mixed concrete delivery problems
Companies in the concrete industry are facing the following scheduling problem on a daily basis: concrete produced at several plants has to be delivered at customers' constru...
Verena Schmid, Karl F. Doerner, Richard F. Hartl, ...
JMLR
2010
147views more  JMLR 2010»
13 years 2 months ago
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
Rahul Mazumder, Trevor Hastie, Robert Tibshirani
BMCBI
2010
135views more  BMCBI 2010»
13 years 7 months ago
MrsRF: an efficient MapReduce algorithm for analyzing large collections of evolutionary trees
Background: MapReduce is a parallel framework that has been used effectively to design largescale parallel applications for large computing clusters. In this paper, we evaluate th...
Suzanne Matthews, Tiffani L. Williams