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» Interpreting distributed ontologies
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UAI
2004
13 years 11 months ago
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
Amir Globerson, Naftali Tishby
ATAL
2010
Springer
13 years 10 months ago
Generation and analysis of multiple futures with swarming agents
Most agent-based modeling techniques generate only a single trajectory in each run, greatly undersampling the space of possible trajectories. Swarming agents can explore a great m...
H. Van Dyke Parunak
IJON
2008
156views more  IJON 2008»
13 years 9 months ago
Structural identifiability of generalized constraint neural network models for nonlinear regression
Identifiability becomes an essential requirement for learning machines when the models contain physically interpretable parameters. This paper presents two approaches to examining...
Shuang-Hong Yang, Bao-Gang Hu, Paul-Henry Courn&eg...
NCA
2006
IEEE
13 years 9 months ago
Open-loop regulation and tracking control based on a genealogical decision tree
The goal of this paper is to design a new control algorithm for open-loop control of complex systems. This control approach is based on a genealogical decision tree for both regula...
Kaddour Najim, Enso Ikonen, P. Del Moral
IJCV
1998
163views more  IJCV 1998»
13 years 9 months ago
CONDENSATION - Conditional Density Propagation for Visual Tracking
The problem of tracking curves in dense visual clutter is challenging. Kalman filtering is inadequate because it is based on Gaussian densities which, being unimodal, cannot repre...
Michael Isard, Andrew Blake