Our institute member Assoc. Dr. Gülşen Taşkın Kaya's study named “A Feature Selection Method via Graph Embedding and Global Sensitivity Analysis” was published in the journal named IEEE Geoscience and Remote Sensing Letter.
This study introduces an FS approach based on graph embedding (GE) and global sensitivity analysis, utilizing the first-order terms of the high dimensional model representation (HDMR). The results of this study show that the proposed method typically outperforms the others and is notably more computationally efficient.
DOI: 10.1109/LGRS.2022.3221536