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BERT for Long Documents: A Case Study of Automated ICD Coding
Transformer models have achieved great success across many NLP problems.
Shaping latent representations using Self-Organizing Maps with Relevance Learning
In this sense, models based on Self-Organizing Maps models with relevance learning (SOMRL) were considered as they perform well in clustering besides being able to create a map that learns the relevance of each input dimension for each cluster, preserving the original relations and topology of the data.
Search Data Structure Learning
In this work, we propose Search Data Structure Learning (SDSL), a generalization of the standard Search Data Structure (SDS) in which the machine has to learn how to search in the database.
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