5 search results - page 1 / 1 » Less is More: Compact Matrix Decomposition for Large Sparse ... |
SDM
2007
SIAM
13 years 6 months ago
2007
SIAM
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...
ICASSP
2010
IEEE
13 years 5 months ago
2010
IEEE
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...
KDD
2008
ACM
14 years 5 months ago
2008
ACM
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
PE
2011
Springer
12 years 11 months ago
2011
Springer
High-level semi-Markov modelling paradigms such as semi-Markov stochastic Petri nets and process algebras are used to capture realistic performance models of computer and communic...
CP
2003
Springer
13 years 10 months ago
2003
Springer
Multiple sequence alignment is a central problem in Bioinformatics. A known integer programming approach is to apply branch-and-cut to exponentially large graph-theoretic models. T...