The ALDEN approach for text classification is a method of active learning that uses diverse interpretations of DNNs and linearly separable regions of samples to determine which unlabeled samples to query for their labels. This approach allows for more efficient and accurate text classification.
What is ALDEN?
ALDEN stands for Active Learning with DivErse iNterpretations, which is a method of active learning for text classification. This approach relies on local interpretations in DNNs to iden
Dual Contrastive Learning (DualCL) is a framework used for representation learning in unsupervised settings, which involves the simultaneous learning of input features and classifier parameters. While contrastive learning has been successful in unsupervised learning, DualCL looks to extend its applicability to supervised learning tasks.
The Challenge of Adapting Contrastive Learning to Supervised Learning
Supervised learning tasks, unlike unsupervised tasks, require labeled data sets, which a
What is MixText and How Does it Work?
Text classification involves the categorization of a given text into one of several predefined classes. This categorization can be done manually by human experts or automatically by computer programs using various algorithms. One popular method is supervised learning, in which a machine is trained to classify texts based on labeled data. However, labeled data can be expensive and time-consuming to obtain. Semi-supervised learning, on the other hand, uses bo