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IJCAI
2001
13 years 10 months ago
Active Learning for Structure in Bayesian Networks
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Simon Tong, Daphne Koller
JMLR
2006
145views more  JMLR 2006»
13 years 9 months ago
Ensemble Pruning Via Semi-definite Programming
An ensemble is a group of learning models that jointly solve a problem. However, the ensembles generated by existing techniques are sometimes unnecessarily large, which can lead t...
Yi Zhang 0006, Samuel Burer, W. Nick Street
BICA
2010
13 years 3 months ago
Validating a High Level Behavioral Representation Language (HERBAL): A Docking Study for ACT-R
We present a docking study for Herbal, a high-level behavioral representation language based on the problem space computational model. This study docks an ACT-R model created with ...
Changkun Zhao, Jaehyon Paik, Jonathan H. Morgan, F...
ICASSP
2007
IEEE
14 years 3 months ago
Evolutionary Sequence Modeling for Discovery of Peptide Hormones
There are currently a large number of ‘‘orphan’’ G-protein-coupled receptors (GPCRs) whose endogenous ligands (peptide hormones) are unknown. Identification of these pepti...
M. Kemal Sönmez, Lawrence Toll, Nina Zaveri
NN
2010
Springer
189views Neural Networks» more  NN 2010»
13 years 3 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