Name
Abstract | ||
|---|---|---|
We investigate the use of an artificial neural network to form a sparse distributed representation of the underlying factors in data sets. We extend the previously proposed (1) network so that it may identify composite causes in data sets by creating a hierarchical network. We use the network as a means of identifying individual faces when the network is trained on a mixture of faces and show both analytically and through experiments how noise allows us to find precisely the factors without prior assumptions of the number of factors. |
Year | Venue | Keywords |
|---|---|---|
1999 | ESANN | artificial neural network,neural network |
Field | DocType | Citations |
Network formation,Data mining,Data set,Computer science,Stochastic neural network,Network simulation,Time delay neural network,Artificial intelligence,Artificial neural network,Nervous system network models,Pattern recognition,Probabilistic neural network,Machine learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Donald Macdonald | 1 | 117 | 9.79 |
| Darryl Charles | 2 | 85 | 16.25 |
| Colin Fyfe | 3 | 508 | 55.62 |