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» Inference Algorithms for Similarity Networks
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SOCIALCOM
2010
14 years 7 months ago
Measuring Similarity between Sets of Overlapping Clusters
The typical task of unsupervised learning is to organize data, for example into clusters, typically disjoint clusters (eg. the K-means algorithm). One would expect (for example) a...
Mark K. Goldberg, Mykola Hayvanovych, Malik Magdon...
GECCO
2005
Springer
127views Optimization» more  GECCO 2005»
15 years 3 months ago
Identifying valid solutions for the inference of regulatory networks
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. The problem often is multi-modal and therefore appropriate optimi...
Christian Spieth, Felix Streichert, Nora Speer, An...
ICASSP
2007
IEEE
15 years 4 months ago
Genomic Network Tomography
This paper considers the problem of learning cellular signaling networks from incomplete measurements of pathway activity. Cells respond to environmental changes (e.g., starvation...
Michael G. Rabbat, Mário A. T. Figueiredo, ...
IJCAI
2003
14 years 11 months ago
Optimal Time-Space Tradeoff in Probabilistic Inference
Recursive Conditioning, RC, is an any-space algorithm lor exact inference in Bayesian networks, which can trade space for time in increments of the size of a floating point number...
David Allen, Adnan Darwiche
CONEXT
2006
ACM
15 years 3 months ago
Inferring groups of correlated failures
We compare and evaluate different methods to infer groups of correlated failures. These methods try to group failure events occurring nearly simultaneously in clusters. Indeed if...
Jean Lepropre, Guy Leduc