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» Algorithms for Large, Sparse Network Alignment Problems
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TNN
2010
176views Management» more  TNN 2010»
13 years 2 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 8 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
KELSI
2004
Springer
14 years 1 months ago
A Randomized Algorithm for Distance Matrix Calculations in Multiple Sequence Alignment
Multiple sequence alignment (MSA) is a vital problem in biology. Optimal alignment of multiple sequences becomes impractical even for a modest number of sequences [1] since the gen...
Sanguthevar Rajasekaran, Vishal Thapar, Hardik Dav...
RECOMB
2006
Springer
14 years 8 months ago
Simple and Fast Inverse Alignment
For as long as biologists have been computing alignments of sequences, the question of what values to use for scoring substitutions and gaps has persisted. While some choices for s...
John D. Kececioglu, Eagu Kim
ICPP
2006
IEEE
14 years 1 months ago
Designing Multithreaded Algorithms for Breadth-First Search and st-connectivity on the Cray MTA-2
stractions are extensively used to understand and solve challenging computational problems in various scientific and engineering domains. They have particularly gained prominence...
David A. Bader, Kamesh Madduri