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ECML
2003
Springer
15 years 7 months ago
Robust k-DNF Learning via Inductive Belief Merging
A central issue in logical concept induction is the prospect of inconsistency. This problem may arise due to noise in the training data, or because the target concept does not fit...
Frédéric Koriche, Joël Quinquet...
KDD
1998
ACM
118views Data Mining» more  KDD 1998»
15 years 6 months ago
A Belief-Driven Method for Discovering Unexpected Patterns
Several pattern discovery methods proposed in the data mining literature have the drawbacks that they discover too many obvious or irrelevant patterns and that they do not leverag...
Balaji Padmanabhan, Alexander Tuzhilin
JMLR
2006
125views more  JMLR 2006»
15 years 1 months ago
Linear Programming Relaxations and Belief Propagation - An Empirical Study
The problem of finding the most probable (MAP) configuration in graphical models comes up in a wide range of applications. In a general graphical model this problem is NP hard, bu...
Chen Yanover, Talya Meltzer, Yair Weiss
IJON
2010
189views more  IJON 2010»
15 years 13 days ago
Inference and parameter estimation on hierarchical belief networks for image segmentation
We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains...
Christian Wolf, Gérald Gavin
ICML
2009
IEEE
16 years 2 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...