Prof. Geoff Webb, the Editor-in-Chief of Data Mining and Knowledge Discovery (Springer) announced in his kdnuggets website that our paper “Manifold Elastic Net: A Unified Framework for Sparse Dimension Reduction”, which was published on DMKD journal in 2011 and cited for 94 times in 2 years, is selected among the top five Editor’s Choice papers for free reading in DMKD journal. So now you can access the full paper from Springer official site before May 31, 2013. Thank you Prof. Webb!
The proposed Manifold Elastic Net (MEN) in the paper provides an efficient and interesting method for building a whole solution path for sparse dimension reduction problems, including most manifold learning methods whose solutions are preferred to be sparse. A dynamic process of selecting real features in building sparse representation/projection matrix can be shown by MEN, which has never been shown in previous sparse PCA methods.