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Obtaining psychological embeddings through joint kernel and metric learning
Psychological embeddings provide a powerful formalism for characterizing human-perceived similarity among members of a stimulus set. Obtaining high-quality embeddings can be costly due to algorithm design, software deployment, and participant compensation. This work aims to advance state-of-the-art...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797663/ https://www.ncbi.nlm.nih.gov/pubmed/31432329 http://dx.doi.org/10.3758/s13428-019-01285-3 |