2020
Learning Surrogates via Deep Embedding
ECCV 2020poster
This paper proposes a technique for training neural networks by minimizing surrogate losses that approximate the target evaluation metric, which may be non-differentiable. The surrogates are learned via a deep embedding where the Euclidean distance between the prediction and the ground truth corresp…