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FPL
2009
Springer
156views Hardware» more  FPL 2009»
15 years 3 months ago
A highly scalable Restricted Boltzmann Machine FPGA implementation
Restricted Boltzmann Machines (RBMs) — the building block for newly popular Deep Belief Networks (DBNs) — are a promising new tool for machine learning practitioners. However,...
Sang Kyun Kim, Lawrence C. McAfee, Peter L. McMaho...
ICML
2009
IEEE
16 years 8 hour ago
Factored conditional restricted Boltzmann Machines for modeling motion style
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 ...
Graham W. Taylor, Geoffrey E. Hinton
ICPR
2010
IEEE
15 years 2 months ago
Deep Belief Networks for Real-Time Extraction of Tongue Contours from Ultrasound During Speech
Ultrasound has become a useful tool for speech scientists studying mechanisms of language sound production. State-of-the-art methods for extracting tongue contours from ultrasound...
Ian Fasel, Jeff Berry
JMLR
2012
13 years 1 months ago
Multiple Texture Boltzmann Machines
We assess the generative power of the mPoTmodel of [10] with tiled-convolutional weight sharing as a model for visual textures by specifically training on this task, evaluating m...
Jyri J. Kivinen, Christopher K. I. Williams
NIPS
2007
15 years 19 days ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun