Flexible Sparse Learning of Feature Subspaces
It is widely observed that the performances of many traditional statistical learning methods degenerate when confronted with high-dimensional data. One promising approach to prevent this downfall is to identify the intrinsic low-dimensional spaces where the true signals embed and to pursue the learn...
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| Language: | English |
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2017
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| Online Access: | https://doi.org/10.7916/D83X8CBB |