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Updated: Jan 29, 2026

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Aprendizaje Positivo-No Etiquetado en Retroalimentación Implícita desde la Perspectiva de Datos Faltantes No
Sichao Wang1, Tianyu Xia2, Lingxiao Yang3
1KUKA Robotics China Co., Ltd., Shanghai 201702, China.
Entropy (Basel, Switzerland)
|January 28, 2026
Resumen
Este estudio aborda el desafío de las etiquetas negativas faltantes en los sistemas de recomendación (SR) formulándolo como un problema de aprendizaje positivo-no etiquetado (PU). Se propone un novedoso marco de despolarización de dos fases para mejorar la robustez del modelo contra confundidores no medidos.
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