Deep Learning, Artificial Intelligence, Self Supervised Learning, Clustering, Contrastive Learning.
denoted by Q=[q1, …, qB], and Q is optimized to maximize the similarity between the features and the prototypes , i.e. (Eq. 3): where H is the entropy function and ε is smoothness parameter. Authors adopt SeLA SSL approach, i.e. Sinkhorn Distance, to work on minibatches by restricting the