We introduce a new class of recurrent, truly sequential SVM-like devices with internal adaptive states, trained by a novel method called EVOlution of systems with KErnel-based outputs (Evoke), an instance of the recent Evolino class of methods. Evoke evolves recurrent networks to detect and represent temporal dependencies while using SVM to produce precise outputs. Evoke is the first SVM-based mechanism learning to classify a context-sensitive language. It also outperforms recent state-of-the-art gradient-based recurrent neural networks (RNNs) on various time series prediction tasks.
|Original language||English (US)|
|Title of host publication||ESANN 2006 Proceedings - European Symposium on Artificial Neural Networks|
|Number of pages||6|
|State||Published - Jan 1 2006|