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» Learning with Temporary Memory
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ICML
2009
IEEE
15 years 4 months ago
Using fast weights to improve persistent contrastive divergence
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
Tijmen Tieleman, Geoffrey E. Hinton
73
Voted
HICSS
2008
IEEE
151views Biometrics» more  HICSS 2008»
15 years 4 months ago
A Conceptual Framework of Transactive Networks System
A virtual organization is a temporary network of companies, which implies the potential opportunity to learn and share abundant sources of complementary and compatible knowledge p...
Sheng-cheng Lin, Yu-Min Wang, Daniel Y. Shee
NN
2008
Springer
153views Neural Networks» more  NN 2008»
14 years 9 months ago
A biologically motivated visual memory architecture for online learning of objects
We present a biologically motivated architecture for object recognition that is based on a hierarchical feature-detection model in combination with a memory architecture that impl...
Stephan Kirstein, Heiko Wersing, Edgar Körner
ACL
2003
14 years 11 months ago
Text Chunking by Combining Hand-Crafted Rules and Memory-Based Learning
This paper proposes a hybrid of handcrafted rules and a machine learning method for chunking Korean. In the partially free word-order languages such as Korean and Japanese, a smal...
Seong-Bae Park, Byoung-Tak Zhang
WCAE
2006
ACM
15 years 3 months ago
Web memory hierarchy learning and research environment
Learning the various structures and levels of memory hierarchy by means of conventional procedures is a complex subject. A memory hierarchy environment (Web-MHE) was proposed and ...
José Leandro D. Mendes, Luiza M. N. Coutinh...