45 search results - page 4 / 9 » Tensor-Variate Restricted Boltzmann Machines |
213
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JMLR
2010
15 years 2 months ago
2010
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
194
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FPL
2009
Springer
16 years 2 days ago
2009
Springer
Restricted Boltzmann Machines (RBMs) — the building block for newly popular Deep Belief Networks (DBNs) — are a promising new tool for machine learning practitioners. However,...
184
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ICML
2009
IEEE
16 years 8 months ago
2009
IEEE
The Conditional Restricted Boltzmann Machine (CRBM) is a recently proposed model for time series that has a rich, distributed hidden state and permits simple, exact inference. We ...
194
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ICML
2010
IEEE
15 years 8 months ago
2010
IEEE
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
208
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FPL
2009
Springer
16 years 2 days ago
2009
Springer
Although there are many neural network FPGA architectures, there is no framework for designing large, high-performance neural networks suitable for the real world. In this paper, ...