1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2023
A two-head loss function for deep Average-K classification
Camille Garcin, Maximilien Servajean, Alexis Joly +1
Average-K classification is an alternative to top-K classification in which the number of labels returned varies with the ambiguity of the input image but must average to K over al…
stat.ML2022★ 1 cited
Stochastic smoothing of the top-K calibrated hinge loss for deep imbalanced classification
Camille Garcin, Maximilien Servajean, Alexis Joly +1
In modern classification tasks, the number of labels is getting larger and larger, as is the size of the datasets encountered in practice. As the number of classes increases, class…