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NIPS
1998
13 years 8 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
ICAIL
2007
ACM
13 years 11 months ago
The Legal-RDF Ontology. A Generic Model for Legal Documents
Legal-RDF.org1 publishes a practical ontology that models both the layout and content of a document and metadata about the document; these have been built using data models implici...
John McClure
TSP
2010
13 years 2 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
PAMI
2007
156views more  PAMI 2007»
13 years 7 months ago
Selection and Fusion of Color Models for Image Feature Detection
—The choice of a color model is of great importance for many computer vision algorithms (e.g., feature detection, object recognition, and tracking) as the chosen color model indu...
Harro M. G. Stokman, Theo Gevers
CVPR
2005
IEEE
14 years 9 months ago
Selection and Fusion of Color Models for Feature Detection
The choice of a color space is of great importance for many computer vision algorithms (e.g. edge detection and object recognition). It induces the equivalence classes to the actu...
Harro M. G. Stokman, Theo Gevers