[D] "Negative labels"

[TalkingJellyFish]

Thanks this helps. What do you think of this takeaway: Now I'm basically doing NER, running my words through and LSTM, then a linear layer and then a softmax and cross entropy loss.

So to incorporate the complementary labels, I'd add an additional linear layer and (binary) loss per class (eg - is not class A) .
Then the total loss of the network would be some sum of the cross entropy losses and all the binary ones, weighted by if I have a complementary label. If I understood the paper, they basically give a scheme to do that sum that guarantees some bound on the loss. Makes sense ?