A Parameter Update Balancing Algorithm for Multi-task Ranking Models in Recommendation Systems

Multi-task ranking models have become essential for modern real-world recommendation systems. While most recommendation researches focus on designing sophisticated models for specific scenarios, achieving performance improvement for multi-task ranking models across various scenarios still remains a...

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Veröffentlicht in:	arXiv.org 2024-10
Hauptverfasser:	Yuan, Jun, Cai, Guohao, Dong, Zhenhua
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Balancing Benchmarks Computer vision Datasets Design optimization Learning Parameters Ranking Recommender systems
Online-Zugang:	Volltext
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