11 search results - page 1 / 3 » Rate-coded Restricted Boltzmann Machines for Face Recognitio... |
111
Voted
NIPS
2000
15 years 1 months ago
2000
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
107
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
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 ...
123
click to vote
CVPR
2012
IEEE
13 years 2 months ago
2012
IEEE
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
97
Voted
ICASSP
2010
IEEE
15 years 17 days ago
2010
IEEE
For decades, Hidden Markov Models (HMMs) have been the state-of-the-art technique for acoustic modeling despite their unrealistic independence assumptions and the very limited rep...
121
Voted
CVPR
2009
IEEE
16 years 7 months ago
2009
IEEE
In this paper we present a method for learning classspecific
features for recognition. Recently a greedy layerwise
procedure was proposed to initialize weights of deep
belief ne...