LGJan 27, 2013
Hierarchical Data Representation Model - Multi-layer NMF
arXiv:1301.6316v314 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental improvement for data representation in document and image analysis.
The paper tackles hierarchical feature learning by extending non-negative matrix factorization into multiple layers, achieving significantly better classification and reconstruction performance with small feature sets.
In this paper, we propose a data representation model that demonstrates hierarchical feature learning using nsNMF. We extend unit algorithm into several layers. Experiments with document and image data successfully discovered feature hierarchies. We also prove that proposed method results in much better classification and reconstruction performance, especially for small number of features. feature hierarchies.