DFFM: Domain Facilitated Feature Modeling for CTR Prediction-Reference-Cited by-同舟云学术

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DFFM: Domain Facilitated Feature Modeling for CTR Prediction

Published:2023-10-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
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Author:

Guo Wei¹^ORCID,Zhu Chenxu¹^ORCID,Yan Fan¹^ORCID,Chen Bo²^ORCID,Liu Weiwen¹^ORCID,Guo Huifeng¹^ORCID,Zheng Hongkun³^ORCID,Liu Yong¹^ORCID,Tang Ruiming¹^ORCID

Affiliation:

1. Huawei Noah's Ark Lab, Huawei, Shanghai, China

2. Huawei Noah's Ark Lab, Shanghai, China

3. Huawei Technologies Co Ltd, Shenzhen, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583780.3615469

Reference33 articles.

1. 2020. MindSpore. https://www.mindspore.cn. 2020. MindSpore. https://www.mindspore.cn.

2. Shai Ben-David , John Blitzer , Koby Crammer , Alex Kulesza , Fernando Pereira , and Jennifer Wortman Vaughan . 2010. A theory of learning from different domains. Machine learning 79 ( 2010 ), 151--175. Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman Vaughan. 2010. A theory of learning from different domains. Machine learning 79 (2010), 151--175.

3. Discriminative learning for differing training and test distributions

4. Rich Caruana . 1997. Multitask learning. Machine learning 28, 1 ( 1997 ), 41--75. Rich Caruana. 1997. Multitask learning. Machine learning 28, 1 (1997), 41--75.

5. Rich Caruana . 1997. Multitask learning. Machine learning 28 ( 1997 ), 41--75. Rich Caruana. 1997. Multitask learning. Machine learning 28 (1997), 41--75.

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