Published as an arXiv preprint, the paper details how unsupervised and self-supervised AI models are matching or surpassing ...

Semi-supervised learning merges supervised and unsupervised methods, enhancing data analysis. This approach uses less labeled data, making it cost-effective yet precise in pattern recognition.

Federated Learning (FL) has gained significant attention as a novel distributed machine learning paradigm that enables collaborative model training while preserving data privacy. However, traditional ...

Self-supervised models generate implicit labels from unstructured data rather than relying on labeled datasets for supervisory signals. Self-supervised learning (SSL), a transformative subset of ...