Aug 14, 2017 · We propose a dynamic ranking paradigm, named as DNN-MAB, that is composed of a pairwise deep neural network (DNN) \mathit{pre}-ranker connecting a revised ...
Optimizing Gross Merchandise Volume via DNN-MAB Dynamic ...
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A dynamic ranking paradigm, named as DNN-MAB, that is composed of a pairwise deep neural network (DNN) connecting a revised multi-armed bandit (MAB) dynamic ...
Duration: 28:14
Posted: Feb 11, 2018
Posted: Feb 11, 2018
本⽂创造性地提出了⼀个动态排序模型，将DNN 和多臂赌博机（MAB）算法结合起来，可. 以根据⽤户实时的操作反馈，及时调整候选推荐列表，从⽽提升整体的推荐准确率。 本⽂的主要贡献有⼆ ...
Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm. Y Yan, W Guo, M Zhao, J Hu, WP Yan. arXiv preprint arXiv:1708.03993, 2017. 2, 2017.
Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm ... gross merchandise volume and inflation factor, and assesses these relationships.
Aug 5, 2024 · A Joint Dynamic Ranking System with DNN and Vector-based ... Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm.
Jianqiang Yao · Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm · Solving a New 3D Bin Packing Problem with Deep Reinforcement Learning ...
Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm · no code implementations • 14 Aug 2017 • Yan Yan, Wentao Guo, Meng Zhao, Jinghe Hu ...
Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm · Yan ... A dynamic ranking paradigm, named as DNN-MAB, that is composed of a ...