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ALMOB
2006
109views more  ALMOB 2006»
14 years 12 months ago
A novel functional module detection algorithm for protein-protein interaction networks
Background: The sparse connectivity of protein-protein interaction data sets makes identification of functional modules challenging. The purpose of this study is to critically eva...
Woochang Hwang, Young-Rae Cho, Aidong Zhang, Mural...
IPPS
2005
IEEE
15 years 5 months ago
Reducing Power with Performance Constraints for Parallel Sparse Applications
Sparse and irregular computations constitute a large fraction of applications in the data-intensive scientific domain. While every effort is made to balance the computational wor...
Guangyu Chen, Konrad Malkowski, Mahmut T. Kandemir...
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 12 days 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...
CORR
2008
Springer
161views Education» more  CORR 2008»
14 years 10 months ago
Compressed Sensing of Analog Signals
Abstract--A traditional assumption underlying most data converters is that the signal should be sampled at a rate exceeding twice the highest frequency. This statement is based on ...
Yonina C. Eldar
KDD
2012
ACM
183views Data Mining» more  KDD 2012»
13 years 2 months ago
Mining discriminative components with low-rank and sparsity constraints for face recognition
This paper introduces a novel image decomposition approach for an ensemble of correlated images, using low-rank and sparsity constraints. Each image is decomposed as a combination...
Qiang Zhang, Baoxin Li