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» Knowledge Extraction from Local Function Networks
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CVPR
2001
IEEE
16 years 27 days ago
A Weighted Non-Negative Matrix Factorization for Local Representations
This paper presents an improvement of the classical Non-negative Matrix Factorization (NMF) approach, for dealing with local representations of image objects. NMF, when applied to...
David Guillamet, Jordi Vitrià, Marco Bressa...
98
Voted
WIOPT
2010
IEEE
14 years 9 months ago
Effect of limited topology knowledge on opportunistic forwarding in ad hoc wireless networks
—Opportunistic forwarding is a simple scheme for packet routing in ad hoc wireless networks such as duty cycling sensor networks in which reducing energy consumption is a princip...
Prithwish Basu, Saikat Guha
IJAR
2007
130views more  IJAR 2007»
14 years 10 months ago
Bayesian network learning algorithms using structural restrictions
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
Luis M. de Campos, Javier Gomez Castellano
110
Voted
ISMB
1996
15 years 6 days ago
A Knowledge-Based Method for Protein Structure Refinement and Prediction
The native conformation of a protein, in a given environment, is determined entirely by the various interatomic interactions dictated by the amino acid sequence (1-3). We describe...
Shankar Subramaniam, David K. Tcheng, James M. Fen...
CIKM
2010
Springer
14 years 9 months ago
FacetCube: a framework of incorporating prior knowledge into non-negative tensor factorization
Non-negative tensor factorization (NTF) is a relatively new technique that has been successfully used to extract significant characteristics from polyadic data, such as data in s...
Yun Chi, Shenghuo Zhu