### Abstract

Original language | English |
---|---|

Place of Publication | Birmingham |

Publisher | Aston University |

Number of pages | 17 |

ISBN (Print) | NCRG/98/016 |

Publication status | Published - 1998 |

### Keywords

- Training Mixture Density Network
- error function
- gradient information
- parameter space
- applied problem solver

### Cite this

*Mixture density network training by computation in parameter space*. Birmingham: Aston University.

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**Mixture density network training by computation in parameter space.** / Evans, David J.

Research output: Working paper › Technical report

TY - UNPB

T1 - Mixture density network training by computation in parameter space

AU - Evans, David J.

PY - 1998

Y1 - 1998

N2 - Training Mixture Density Network (MDN) configurations within the NETLAB framework takes time due to the nature of the computation of the error function and the gradient of the error function. By optimising the computation of these functions, so that gradient information is computed in parameter space, training time is decreased by at least a factor of sixty for the example given. Decreased training time increases the spectrum of problems to which MDNs can be practically applied making the MDN framework an attractive method to the applied problem solver.

AB - Training Mixture Density Network (MDN) configurations within the NETLAB framework takes time due to the nature of the computation of the error function and the gradient of the error function. By optimising the computation of these functions, so that gradient information is computed in parameter space, training time is decreased by at least a factor of sixty for the example given. Decreased training time increases the spectrum of problems to which MDNs can be practically applied making the MDN framework an attractive method to the applied problem solver.

KW - Training Mixture Density Network

KW - error function

KW - gradient information

KW - parameter space

KW - applied problem solver

M3 - Technical report

SN - NCRG/98/016

BT - Mixture density network training by computation in parameter space

PB - Aston University

CY - Birmingham

ER -