The Sequence Scope: The Fight Against Labeled Dataset Dependencies

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📝 Editorial: The Fight Against Labeled Dataset Dependencies

Supervised learning has dominated the world of machine learning (ML) for the last few decades. The predominance of supervised models in mainstream ML applications seems logical considering that they are easier to model, interpret, and optimize than the non-supervised alternatives. However, supervised ML models have the big limitation of their dependency on large, labeled datasets which are very expensive to build and maintain. The dependencies on labeled data are not only technological but also economical as it has made ML research a privilege of large organizations with access to highly curated datasets. To that, we should add that supervised learning paradigms are not particularly…