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FairWASP: Fast and Optimal Fair Wasserstein Pre-processing

Fuente: arXiv

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Detalles Bibliográficos
Autores principales:	Xiong, Zikai, Dalmasso, Niccolò, Mishler, Alan, Potluru, Vamsi K., Balch, Tucker, Veloso, Manuela
Formato:	Preprint
Publicado:	2023
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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