K-Means Clustering can partition unlabeled data based on distance into groups of similar datapoints automatically. The distance can be euclidean.

Real AM-Softmax loss function is an improvement of AM-Softmax. It is proposed in paper: Real Additive Margin Softmax for Speaker Verification.

AAM-Softmax is also called ArcFace and is proposed in paper: ArcFace: Additive Angular Margin Loss for Deep Face Recognition.

DAM-Softmax loss is an improvement of AM-Softmax, it is proposed in paper: Dynamic Margin Softmax Loss for Speaker Verification.

AM-Softmax Loss is also called additive margin softmax. It is an improvement of softmax loss and proposed in paper: Additive Margin Softmax for Face Verification.

OC-Softmax loss function is proposed in paper: One-class Learning Towards Synthetic Voice Spoofing Detection. It often be used in synthetic voice spoofing detection task.

Agreement loss is proposed in paper: Learning from Noisy Labels for Entity-Centric Information Extraction. It is a regularization method.