45 search results - page 4 / 9 » Tensor-Variate Restricted Boltzmann Machines |
128
Voted
JMLR
2010
14 years 7 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...
111
Voted
FPL
2009
Springer
15 years 5 months 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,...
103
Voted
ICML
2009
IEEE
16 years 1 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 ...
111
Voted
ICML
2010
IEEE
15 years 1 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 ...
112
Voted
FPL
2009
Springer
15 years 5 months 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, ...