Transcription of Boltzmann Machines
{{id}} {{{paragraph}}}
Example: air traffic controller
Boltzmann Machines
Boltzmann Machines Geoffrey E. Hinton March 25, 2007. A Boltzmann Machine is a network of symmetrically connected, neuron- like units that make stochastic decisions about whether to be on or off. Boltz- mann Machines have a simple learning algorithm that allows them to discover interesting features in datasets composed of binary vectors. The learning al- gorithm is very slow in networks with many layers of feature detectors, but it can be made much faster by learning one layer of feature detectors at a time. Boltzmann Machines are used to solve two quite different computational problems. For a search problem, the weights on the connections are fixed and are used to represent the cost function of an optimization problem.
Conditional Boltzmann machines Boltzmann machines model the distribution of the data vectors, but there is a simple extension for modelling conditional distributions (Ackley et al., 1985). The only di erence between the visible and the hidden units is that, when sampling hsisjidata, the visible units are clamped and the hidden units are not.
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: