Tag Archives: multi-label learning

Compressed Labeling: An important extension of Hamming Compressed Sensing; at NIPS now

We are just informed that our submission “Compressed Labeling (CL) on Distilled Labelsets (DL) for Multi-label Learning” is accepted by Machine Learning Journal (Springer). Online first PDF can be downloaded here. CL is an important application and extension of Hamming … 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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