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COMBINATORICS
2006
107views more  COMBINATORICS 2006»
13 years 9 months ago
The Linear Complexity of a Graph
The linear complexity of a matrix is a measure of the number of additions, subtractions, and scalar multiplications required to multiply that matrix and an arbitrary vector. In th...
David L. Neel, Michael E. Orrison
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 10 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...
ICASSP
2010
IEEE
13 years 9 months ago
Fast signal analysis and decomposition on graphs using the Sparse Matrix Transform
Recently, the Sparse Matrix Transform (SMT) has been proposed as a tool for estimating the eigen-decomposition of high dimensional data vectors [1]. The SMT approach has two major...
Leonardo R. Bachega, Guangzhi Cao, Charles A. Boum...
CORR
2011
Springer
199views Education» more  CORR 2011»
13 years 3 months ago
Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining
Scaling up the sparse matrix-vector multiplication kernel on modern Graphics Processing Units (GPU) has been at the heart of numerous studies in both academia and industry. In thi...
Xintian Yang, Srinivasan Parthasarathy, Ponnuswamy...
COCOON
2003
Springer
14 years 2 months ago
The Complexity of Boolean Matrix Root Computation
Abstract. We show that finding roots of Boolean matrices is an NPhard problem. This answers a twenty year old question from semigroup theory. Interpreting Boolean matrices as dire...
Martin Kutz