Fast learning method for RAAM based on sensitivity analysis

A. Barcz

doi:10.1117/12.2074625

25 November 2014 Fast learning method for RAAM based on sensitivity analysis

A. Barcz

Author Affiliations +

Proceedings Volume 9290, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2014; 92902R (2014) https://doi.org/10.1117/12.2074625
Event: Symposium on Photonics Applications in Astronomy, Communications, Industry and High-Energy Physics Experiments, 2014, Warsaw, Poland

Abstract

This article presents a novel combination of the Recursive Auto-Associative Memory model with the Sensitivity- Based Linear Learning Method. Training results on the syntactic trees dataset are presented, confirming that the application of the SBLLM method to the RAAM model results in very fast learning and yields clustering results of the same quality as the original RAAM model.

Citation Download Citation

A. Barcz "Fast learning method for RAAM based on sensitivity analysis", Proc. SPIE 9290, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2014, 92902R (25 November 2014); https://doi.org/10.1117/12.2074625

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