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 labels of a few samples incorrect (i. https://herbsdailyes.shop/product-category/mustard/