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KDD
2009
ACM
179views Data Mining» more  KDD 2009»
16 years 26 days ago
Identifying graphs from noisy and incomplete data
There is a growing wealth of data describing networks of various types, including social networks, physical networks such as transportation or communication networks, and biologic...
Galileo Mark S. Namata Jr., Lise Getoor
BMCBI
2006
202views more  BMCBI 2006»
15 years 6 months ago
Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks
Background: The learning of global genetic regulatory networks from expression data is a severely under-constrained problem that is aided by reducing the dimensionality of the sea...
David J. Reiss, Nitin S. Baliga, Richard Bonneau
ENVSOFT
2008
175views more  ENVSOFT 2008»
15 years 6 months ago
Automated regression-based statistical downscaling tool
Many impact studies require climate change information at a finer resolution than that provided by Global Climate Models (GCMs). In the last 10 years, downscaling techniques, both...
Masoud Hessami, Philippe Gachon, Taha B. M. J. Oua...
ICML
2007
IEEE
16 years 7 months ago
Recovering temporally rewiring networks: a model-based approach
A plausible representation of relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network which is topologically r...
Fan Guo, Steve Hanneke, Wenjie Fu, Eric P. Xing
PAMI
2011
15 years 1 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams