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» Ensemble Methods in Machine Learning
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ASC
2006
13 years 8 months ago
Speeding up the learning of equivalence classes of bayesian network structures
For some time, learning Bayesian networks has been both feasible and useful in many problems domains. Recently research has been done on learning equivalence classes of Bayesian n...
Rónán Daly, Qiang Shen, J. Stuart Ai...
ACL
2008
13 years 10 months ago
Large Scale Acquisition of Paraphrases for Learning Surface Patterns
Paraphrases have proved to be useful in many applications, including Machine Translation, Question Answering, Summarization, and Information Retrieval. Paraphrase acquisition meth...
Rahul Bhagat, Deepak Ravichandran
AAAI
2006
13 years 9 months ago
kFOIL: Learning Simple Relational Kernels
A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FO...
Niels Landwehr, Andrea Passerini, Luc De Raedt, Pa...
CORR
2008
Springer
100views Education» more  CORR 2008»
13 years 8 months ago
Learning Isometric Separation Maps
Maximum Variance Unfolding (MVU) and its variants have been very successful in embedding data-manifolds in lower dimensionality spaces, often revealing the true intrinsic dimensio...
Nikolaos Vasiloglou, Alexander G. Gray, David V. A...
JMLR
2008
139views more  JMLR 2008»
13 years 8 months ago
Regularization on Graphs with Function-adapted Diffusion Processes
Harmonic analysis and diffusion on discrete data has been shown to lead to state-of-theart algorithms for machine learning tasks, especially in the context of semi-supervised and ...
Arthur D. Szlam, Mauro Maggioni, Ronald R. Coifman