Tag Archives: sparse learning

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 … Continue reading

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Semi-Soft GoDec: >4 times faster, auto-determined k

Here is a good news of GoDec (pertaining to our ICML 2011 paper): Semi-Soft GoDec is released. Different from the ordinary GoDec which imposes hard threshholding to both the singular values of the low-rank part L and the entries of the … Continue reading

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GoDec: Randomized Low-rank & Sparse Matrix Decomposition in Noisy Case

This paper is accepted by ICML 2011 for presentation. Now the final version is ready and can be downloaded from here GO. Abstract: Low-rank and sparse structures have been profoundly studied in matrix completion and compressed sensing. In this paper, we develop … Continue reading

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Multi-label Learning via Structured Decomposition and Group Sparsity

This paper is now available on arxiv: http://arxiv.org/abs/1103.0102 In multi-label learning, each sample is associated with several labels. Existing works indicate that exploring correlations between labels improve the prediction performance. However, embedding the label correlations into the training process significantly … Continue reading

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Manifold Elastic Net: A Unified Framework for Sparse Dimension Reduction

Manifold Elastic Net is the work we have done one year ago and it is about to be published on Data Mining and Knowledge Discovery (Springer) recently. You can either find it on the website of DMKD: http://www.springerlink.com/content/bk6301u1938104q6/ or the … Continue reading

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