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» An Analysis of Rule Evaluation Metrics
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ML
2006
ACM
142views Machine Learning» more  ML 2006»
13 years 7 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
PAMI
1998
100views more  PAMI 1998»
13 years 7 months ago
Hilbert-Schmidt Lower Bounds for Estimators on Matrix Lie Groups for ATR
—Deformable template representations of observed imagery, model the variability of target pose via the actions of the matrix Lie groups on rigid templates. In this paper, we stud...
Ulf Grenander, Michael I. Miller, Anuj Srivastava
GECCO
2011
Springer
270views Optimization» more  GECCO 2011»
12 years 11 months ago
Geometric surrogate-based optimisation for permutation-based problems
In continuous optimisation, surrogate models (SMs) are used when tackling real-world problems whose candidate solutions are expensive to evaluate. In previous work, we showed that...
Alberto Moraglio, Yong-Hyuk Kim, Yourim Yoon
EDBT
2009
ACM
96views Database» more  EDBT 2009»
14 years 2 months ago
Top-k dominant web services under multi-criteria matching
As we move from a Web of data to a Web of services, enhancing the capabilities of the current Web search engines with effective and efficient techniques for Web services retrieva...
Dimitrios Skoutas, Dimitris Sacharidis, Alkis Simi...
COMCOM
2008
99views more  COMCOM 2008»
13 years 8 months ago
Efficiently reconfigurable backbones for wireless sensor networks
We present the definition and performance evaluation of a protocol for building and maintaining a connected backbone among the nodes of a wireless sensor networks (WSN). Building ...
Stefano Basagni, Chiara Petrioli, Roberto Petrocci...