Zobrazeno 1 - 10
of 236
pro vyhledávání: '"Zhang, XiuWu"'
Autor:
Ouyang, Wentao, Zhang, Xiuwu, Guo, Chaofeng, Ren, Shukui, Sui, Yupei, Zhang, Kun, Luo, Jinmei, Chen, Yunfeng, Xu, Dongbo, Liu, Xiangzheng, Du, Yanlong
In real-world advertising systems, conversions have different types in nature and ads can be shown in different display scenarios, both of which highly impact the actual conversion rate (CVR). This results in the multi-type and multi-scenario CVR pre
Externí odkaz:
http://arxiv.org/abs/2403.17425
Autor:
Ouyang, Wentao, Dong, Rui, Zhang, Xiuwu, Guo, Chaofeng, Luo, Jinmei, Liu, Xiangzheng, Du, Yanlong
Conversion rate (CVR) prediction plays an important role in advertising systems. Recently, supervised deep neural network-based models have shown promising performance in CVR prediction. However, they are data hungry and require an enormous amount of
Externí odkaz:
http://arxiv.org/abs/2307.05974
Autor:
Liang, Ruiheng, Wu, Huizhong, Hu, Zhongzheng, Sun, Jiangli, Fu, Chunhong, Li, Shuaishuai, Zhang, Xiuwu, Zhou, Minghua
Publikováno v:
In Applied Catalysis B: Environment and Energy 5 September 2024 352
Autor:
Zhang, Xiuwu, Wu, Huizhong, Jing, Jiana, Liu, Jingyang, Li, Shuaishuai, Song, Ge, Liang, Ruiheng, Ren, Xueying, Zhou, Minghua
Publikováno v:
In Applied Catalysis B: Environment and Energy 15 December 2024 359
Publikováno v:
In Chemical Engineering Journal 1 July 2024 491
Publikováno v:
In Journal of Environmental Chemical Engineering June 2024 12(3)
Publikováno v:
In Separation and Purification Technology 5 May 2024 335
Autor:
Ouyang, Wentao, Zhang, Xiuwu, Ren, Shukui, Li, Li, Zhang, Kun, Luo, Jinmei, Liu, Zhaojie, Du, Yanlong
Click-through rate (CTR) prediction is one of the most central tasks in online advertising systems. Recent deep learning-based models that exploit feature embedding and high-order data nonlinearity have shown dramatic successes in CTR prediction. How
Externí odkaz:
http://arxiv.org/abs/2105.08909
Publikováno v:
In Journal of Innovation & Knowledge April-June 2024 9(2)
Publikováno v:
In Technological Forecasting & Social Change March 2024 200