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autoBOT: evolving neuro-symbolic representations for explainable low resource text classification
Learning from texts has been widely adopted throughout industry and science. While state-of-the-art neural language models have shown very promising results for text classification, they are expensive to (pre-)train, require large amounts of data and tuning of hundreds of millions or more parameters...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8550026/ https://www.ncbi.nlm.nih.gov/pubmed/34720391 http://dx.doi.org/10.1007/s10994-021-05968-x |