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246
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NN
2010
Springer
189views Neural Networks» more  NN 2010»
15 years 2 months ago
Sparse kernel learning with LASSO and Bayesian inference algorithm
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
Junbin Gao, Paul W. Kwan, Daming Shi
218
Voted
ICML
2008
IEEE
16 years 8 months ago
Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity
Causal analysis of continuous-valued variables typically uses either autoregressive models or linear Gaussian Bayesian networks with instantaneous effects. Estimation of Gaussian ...
Aapo Hyvärinen, Patrik O. Hoyer, Shohei Shimi...
178
Voted
ICML
2009
IEEE
16 years 8 months ago
Polyhedral outer approximations with application to natural language parsing
Recent approaches to learning structured predictors often require approximate inference for tractability; yet its effects on the learned model are unclear. Meanwhile, most learnin...
André F. T. Martins, Noah A. Smith, Eric P....
189
Voted
ISOLA
2007
Springer
16 years 1 months ago
Using Invariant Detection Mechanism in Black Box Inference
The testing and formal verification of black box software components is a challenging domain. The problem is even harder when specifications of these components are not available...
Muzammil Shahbaz, Roland Groz
190
Voted
FGCN
2008
IEEE
155views Communications» more  FGCN 2008»
15 years 9 months ago
Modeling the Marginal Distribution of Gene Expression with Mixture Models
We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
Edward Wijaya, Hajime Harada, Paul Horton