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» Using model knowledge for learning inverse dynamics
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IJCNN
2007
IEEE
15 years 8 months ago
System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks
— A single biological neuron is able to perform complex computations that are highly nonlinear in nature, adaptive, and superior to the perceptron model. A neuron is essentially ...
Manish Saggar, Tekin Meriçli, Sari Andoni, ...
IJMSO
2007
76views more  IJMSO 2007»
15 years 2 months ago
Towards an automatic monitoring for higher education Learning Design
: The development of new Information Technologies have originated new possibilities to develop pedagogical methodologies that provide the necessary knowledge and skills in the High...
David Camacho, María Dolores Rodrígu...
129
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CVPR
2006
IEEE
16 years 4 months ago
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image
When we look at a picture, our prior knowledge about the world allows us to resolve some of the ambiguities that are inherent to monocular vision, and thereby infer 3d information...
Erick Delage, Honglak Lee, Andrew Y. Ng
SAC
2009
ACM
15 years 9 months ago
Combining statistics and semantics via ensemble model for document clustering
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
113
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INTERSPEECH
2010
14 years 9 months ago
Learning a language model from continuous speech
This paper presents a new approach to language model construction, learning a language model not from text, but directly from continuous speech. A phoneme lattice is created using...
Graham Neubig, Masato Mimura, Shinsuke Mori, Tatsu...