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ICML
2009
IEEE
15 years 12 months ago
Large-scale deep unsupervised learning using graphics processors
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
Rajat Raina, Anand Madhavan, Andrew Y. Ng
IJSEKE
2006
138views more  IJSEKE 2006»
14 years 11 months ago
Towards Automatic Establishment of Model Dependencies Using Formal Concept Analysis
tion and alteration of software models at different levels of abstraction. These modifications are usually performed independently, but the objects to which they are applied to, ar...
Igor Ivkovic, Kostas Kontogiannis
JPDC
2006
106views more  JPDC 2006»
14 years 11 months ago
Performance characteristics of the multi-zone NAS parallel benchmarks
We describe a new suite of computational benchmarks that models applications featuring multiple levels of parallelism. Such parallelism is often available in realistic flow comput...
Haoqiang Jin, Rob F. Van der Wijngaart
NN
2006
Springer
141views Neural Networks» more  NN 2006»
14 years 11 months ago
Encoding uncertainty in the hippocampus
The medial temporal lobe may play a critical role in binding successive events into memory while encoding contextual information in implicit and explicit memory tasks. Information...
Lee M. Harrison, Andrew Duggins, Karl J. Friston
JVCIR
2010
177views more  JVCIR 2010»
14 years 9 months ago
Ripplet: A new transform for image processing
Efficient representation of images usually leads to improvements in storage efficiency, computational complexity and performance of image processing algorithms. Efficient represe...
Jun Xu, Lei Yang, Dapeng Wu