Our DMKD paper is selected as Top 5 Editor’s Choice Article for Free Reading

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.

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About tianyizhou

Research Assistant at University Washington, Seattle, Working on Machine Learning & Statistics in MODE lab leaded by Prof. Carlos Guestrin, and MELODI lab leaded by Prof. Jeff Bilmes.
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One Response to Our DMKD paper is selected as Top 5 Editor’s Choice Article for Free Reading

  1. Igor Carron says:

    Congratulations Tianyi !
    Please let me know If you do make MEN available for download, I’ll feature it widely on Nuit Blanche.

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