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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
16 years 2 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
AMFG
2005
IEEE
203views Biometrics» more  AMFG 2005»
15 years 7 months ago
Learning to Fuse 3D+2D Based Face Recognition at Both Feature and Decision Levels
2D intensity images and 3D shape models are both useful for face recognition, but in different ways. While algorithms have long been developed using 2D or 3D data, recently has see...
Stan Z. Li, ChunShui Zhao, Meng Ao, Zhen Lei
TIT
1998
112views more  TIT 1998»
15 years 1 months ago
Application of Network Calculus to Guaranteed Service Networks
—We use recent network calculus results to study some properties of lossless multiplexing as it may be used in guaranteed service networks. We call network calculus a set of resu...
Jean-Yves Le Boudec
IJIS
2002
112views more  IJIS 2002»
15 years 1 months ago
Integrating fuzzy topological maps and fuzzy geometric maps for behavior-based robots
ior-based robots, planning is necessary to elaborate abstract plans that resolve complex navigational tasks. Usually maps of the environment are used to plan the robot motion and t...
Eugenio Aguirre, Antonio González
125
Voted
JUCS
2006
107views more  JUCS 2006»
15 years 1 months ago
Sequential Data Assimilation: Information Fusion of a Numerical Simulation and Large Scale Observation Data
: Data assimilation is a method of combining an imperfect simulation model and a number of incomplete observation data. Sequential data assimilation is a data assimilation in which...
Kazuyuki Nakamura, Tomoyuki Higuchi, Naoki Hirose