|
Information optimum vector quantization| old_uid | 875 |
|---|
| title | Information optimum vector quantization |
|---|
| start_date | 2006/03/17 |
|---|
| schedule | 12h-13h30 |
|---|
| online | no |
|---|
| location_info | salle 314 |
|---|
| summary | Information optimum data processing is an important task in data analysis and data mining. We consider actual approaches for information optimal vector quantization. These approaches include methods which optimize information theoretic measures like Kullback-Leibler-divergence directly. Further, we show that for neural vector quantizer like self-organizing maps (SOMs) and neural gas (NG) information optimal data processing is possible by magnification control. Thereby, magnification is a property of the vector quantizer which is closely related to the description error by the law discovered by Zador. The effect of information control is demonstrated for several examples. |
|---|
| oncancel | Changement de lieu et d’horaire |
|---|
| responsibles | <not specified> |
|---|
| |
|