Multi-Label Prediction via Compressed Sensing
Hsu, Daniel J., Kakade, Sham M., Langford, John, Zhang, Tong
–Neural Information Processing Systems
We consider multi-label prediction problems with large output spaces under the assumption of output sparsity - that the target (label) vectors have small support. We develop a general theory for a variant of the popular error correcting output code scheme, using ideas from compressed sensing for exploiting this sparsity.
Neural Information Processing Systems
Dec-31-2009