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FPL
2009
Springer
161views Hardware» more  FPL 2009»
14 years 3 months ago
A multi-FPGA architecture for stochastic Restricted Boltzmann Machines
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, ...
Daniel L. Ly, Paul Chow
JMLR
2010
125views more  JMLR 2010»
13 years 5 months ago
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation
In this paper, we consider the asymptotic form of the generalization error for the restricted Boltzmann machine in Bayesian estimation. It has been shown that obtaining the maximu...
Miki Aoyagi
ICML
2010
IEEE
13 years 12 months ago
Rectified Linear Units Improve Restricted Boltzmann Machines
Restricted Boltzmann machines were developed using binary stochastic hidden units. These can be generalized by replacing each binary unit by an infinite number of copies that all ...
Vinod Nair, Geoffrey E. Hinton
FPGA
2009
ACM
201views FPGA» more  FPGA 2009»
14 years 5 months ago
A high-performance FPGA architecture for restricted boltzmann machines
Despite the popularity and success of neural networks in research, the number of resulting commercial or industrial applications have been limited. A primary cause of this lack of...
Daniel L. Ly, Paul Chow
JMLR
2010
123views more  JMLR 2010»
13 years 5 months ago
Inductive Principles for Restricted Boltzmann Machine Learning
Recent research has seen the proposal of several new inductive principles designed specifically to avoid the problems associated with maximum likelihood learning in models with in...
Benjamin Marlin, Kevin Swersky, Bo Chen, Nando de ...