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» Learning Hierarchical Shape Models from Examples
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JMLR
2008
230views more  JMLR 2008»
13 years 7 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
NAACL
2007
13 years 9 months ago
Can Semantic Roles Generalize Across Genres?
PropBank has been widely used as training data for Semantic Role Labeling. However, because this training data is taken from the WSJ, the resulting machine learning models tend to...
Szu-ting Yi, Edward Loper, Martha Palmer
JMLR
2006
131views more  JMLR 2006»
13 years 7 months ago
On Representing and Generating Kernels by Fuzzy Equivalence Relations
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
Bernhard Moser
IPSN
2003
Springer
14 years 27 days ago
Hypothesis Testing over Factorizations for Data Association
Abstract. The issue of data association arises frequently in sensor networks; whenever multiple sensors and sources are present, it may be necessary to determine which observations...
Alexander T. Ihler, John W. Fisher III, Alan S. Wi...
ACIVS
2007
Springer
14 years 1 months ago
Model-Based Image Segmentation for Multi-view Human Gesture Analysis
Multi-camera networks bring in potentials for a variety of vision-based applications through provisioning of rich visual information. In this paper a method of image segmentation f...
Chen Wu, Hamid K. Aghajan