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» Algorithms for Large, Sparse Network Alignment Problems
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JCDL
2006
ACM
176views Education» more  JCDL 2006»
14 years 1 months ago
A hierarchical, HMM-based automatic evaluation of OCR accuracy for a digital library of books
A number of projects are creating searchable digital libraries of printed books. These include the Million Book Project, the Google Book project and similar efforts from Yahoo an...
Shaolei Feng, R. Manmatha
ARC
2007
Springer
123views Hardware» more  ARC 2007»
13 years 11 months ago
Multiple Sequence Alignment Using Reconfigurable Computing
The alignment of multiple protein (or DNA) sequences is a current problem in Bioinformatics. ClustalW is the most popular heuristic algorithm for multiple sequence alignment. Pairw...
Carlos R. Erig Lima, Heitor S. Lopes, Maiko R. Mor...
PKDD
2010
Springer
158views Data Mining» more  PKDD 2010»
13 years 6 months ago
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
Katya Scheinberg, Irina Rish
COLT
2004
Springer
14 years 1 months ago
Regularization and Semi-supervised Learning on Large Graphs
We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
Mikhail Belkin, Irina Matveeva, Partha Niyogi
AAAI
2000
13 years 9 months ago
Divide-and-Conquer Frontier Search Applied to Optimal Sequence Alignment
We present a new algorithm that reduces the space complexity of heuristic search. It is most effective for problem spaces that grow polynomially with problem size, but contain lar...
Richard E. Korf, Weixiong Zhang