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VMCAI
2012
Springer
14 years 2 months ago
A General Framework for Probabilistic Characterizing Formulae
Abstract. Recently, a general framework on characteristic formulae was proposed by Aceto et al. It offers a simple theory that allows one to easily obtain characteristic formulae o...
Joshua Sack, Lijun Zhang
PAMI
1998
86views more  PAMI 1998»
15 years 6 months ago
Spatial Sampling of Printed Patterns
—The bitmap obtained by scanning a printed pattern depends on the exact location of the scanning grid relative to the pattern. We consider ideal sampling with a regular lattice o...
Prateek Sarkar, George Nagy, Jiangying Zhou, Danie...
ICML
2007
IEEE
16 years 7 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney
MLDM
2005
Springer
16 years 8 days ago
Unsupervised Learning of Visual Feature Hierarchies
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
Fabien Scalzo, Justus H. Piater
COLT
2001
Springer
15 years 11 months ago
Smooth Boosting and Learning with Malicious Noise
We describe a new boosting algorithm which generates only smooth distributions which do not assign too much weight to any single example. We show that this new boosting algorithm ...
Rocco A. Servedio