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IMC
2007
ACM
13 years 9 months ago
Learning network structure from passive measurements
The ability to discover network organization, whether in the form of explicit topology reconstruction or as embeddings that approximate topological distance, is a valuable tool. T...
Brian Eriksson, Paul Barford, Robert Nowak, Mark C...
IEEECIT
2010
IEEE
13 years 6 months ago
A Learning Spectrum Hole Prediction Model for Cognitive Radio Systems
—In this paper, we present a new spectrum-hole prediction model for cognitive radio (CR) systems based on the IEEE 802.11 wireless local areas networks. We have also analyzed the...
Zhigang Wen, Chunxiao Fan, Xiaoying Zhang, Yuexin ...
IJCNN
2000
IEEE
14 years 5 days ago
Metrics that Learn Relevance
We introduce an algorithm for learning a local metric to a continuous input space that measures distances in terms of relevance to the processing task. The relevance is defined a...
Samuel Kaski, Janne Sinkkonen
ACML
2009
Springer
14 years 2 months ago
Community Detection on Weighted Networks: A Variational Bayesian Method
Abstract. Massive real-world data are network-structured, such as social network, relationship between proteins and power grid. Discovering the latent communities is a useful way f...
Qixia Jiang, Yan Zhang, Maosong Sun
ACMICEC
2008
ACM
276views ECommerce» more  ACMICEC 2008»
13 years 9 months ago
A Bayesian network for IT governance performance prediction
The goal of IT governance is not only to achieve internal efficiency in an IT organization, but also to support IT's role as a business enabler. The latter is here denoted IT...
Mårten Simonsson, Robert Lagerström, Po...