Robust Cross-View Embedding With Discriminant Structure for Multi-Label Classification
Label embedding is an important family of multi-label classification algorithms which can jointly extract the information of all labels for better performance.However, few works have been done to develop the multi-label embedding methods that can effectively deal with the interference of noisy data during training process.The noise often makes the