Triplet Entropy Loss
2000년 도입 · 논문 1편에서 사용
The Triplet Entropy Loss (TEL) training method aims to leverage both the strengths of Cross Entropy Loss (CEL) and Triplet loss during the training process, assuming that it would lead to better generalization. The TEL method though does not contain a pre-training step, but trains simultaneously with both CEL and Triplet losses.
출처: Triplet Entropy Loss: Improving The Generalisation of Short Speech Language Identification Systems
소개 논문: Triplet Entropy Loss: Improving The Generalisation of Short Speech Language Identification Systems
Loss Functions · General