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Click-through rate (CTR) estimation plays as a core function module in various personalized online services, including online advertising, recommender systems, and web search etc.
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What is personalization? perspectives on the design and implementation of personalization in information systems
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Predicting clicks: estimating the click-through rate for new ads
Matthew Richardson, Ewa Dominowska, and Robert Ragno · 2007
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Training and testing low-degree polynomial data mappings via linear svm
Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang, Michael Ringgaard, and Chih-Jen Lin · 2010
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Factorization machines
Steffen Rendle · 2010
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Deepak Agarwal, Bo Long, Jonathan Traupman, Doris Xin, and Liang Zhang · 2014
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Chen Cheng, Fen Xia, Tong Zhang, Irwin King, and Michael R Lyu · 2014
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A convolutional click prediction model
Qiang Liu, Feng Yu, Shu Wu, and Liang Wang · 2015
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Mathieu Blondel, Akinori Fujino, Naonori Ueda, and Masakazu Ishihata · 2016
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Wide & deep learning for recommender systems
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, et al · 2016
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Yanru Qu, Han Cai, Kan Ren, Weinan Zhang, Yong Yu, Ying Wen, and Jun Wang · 2016
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Deep crossing: Web-scale modeling without manually crafted combinatorial features
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Deep learning over multi-field categorical data: A case study on user response prediction
Weinan Zhang, Tianming Du, and Jun Wang · 2016
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Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, and Xiuqiang He · 2017
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Neural factorization machines for sparse predictive analytics
Xiangnan He and Tat-Seng Chua · 2017
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2017
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Attention is all you need
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Deep & cross network for ad click predictions
Ruoxi Wang, Bin Fu, Gang Fu, and Mingliang Wang · 2017
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Jun Xiao, Hao Ye, Xiangnan He, Hanwang Zhang, Fei Wu, and Tat-Seng Chua · 2017
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Field-weighted factorization machines for click-through rate prediction in display advertising
Junwei Pan, Jian Xu, Alfonso Lobos Ruiz, Wenliang Zhao, Shengjun Pan, Yu Sun, and Quan Lu · 2018
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Product-based neural networks for user response prediction over multi-field categorical data
Differentiable neural input search for recommender systems
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Hui Fang, Danning Zhang, Yiheng Shu, and Guibing Guo · 2020
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Neural input search for large scale recommendation models
Manas R. Joglekar, Cong Li, Mei Chen, Taibai Xu, Xiaoming Wang, Jay K. Adams, Pranav Khaitan, Jiahui Liu, and Quoc V. Le · 2020
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Autofeature: Searching for feature interactions and their architectures for click-through rate prediction
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Interpretable click-through rate prediction through hierarchical attention
Zeyu Li, Wei Cheng, Yang Chen, Haifeng Chen, and Wei Wang · 2020
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Yanru Qu, Bohui Fang, Weinan Zhang, Ruiming Tang, Minzhe Niu, Huifeng Guo, Yong Yu, and Xiuqiang He · 2018
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Deep interest network for click-through rate prediction
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Behavior sequence transformer for e-commerce recommendation in alibaba
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Yifan Chen, Pengjie Ren, Yang Wang, and Maarten de Rijke · 2019
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Deep session interest network for click-through rate prediction
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Fibinet: combining feature importance and bilinear feature interaction for click-through rate prediction
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Autofis: Automatic feature interaction selection in factorization models for click-through rate prediction
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Automated embedding size search in deep recommender systems
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Search-based user interest modeling with lifelong sequential behavior data for click-through rate prediction
Pi Qi, Xiaoqiang Zhu, Guorui Zhou, Yujing Zhang, Zhe Wang, Lejian Ren, Ying Fan, and Kun Gai · 2020
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Jiarui Qin, W. Zhang, Xin Wu, Jiarui Jin, Yuchen Fang, and Y. Yu · 2020
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Neural collaborative filtering vs. matrix factorization revisited
Steffen Rendle, Walid Krichene, Li Zhang, and John Anderson · 2020
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Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, and Xia Hu · 2020
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Ruoxi Wang, Rakesh Shivanna, Derek Z Cheng, Sagar Jain, Dong Lin, Lichan Hong, and Ed H Chi · 2020
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Pengyu Zhao, Kecheng Xiao, Yuanxing Zhang, Kaigui Bian, and Wei Yan · 2020
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Learnable embedding sizes for recommender systems
Siyi Liu, Chen Gao, Yihong Chen, Depeng Jin, and Yong Li · 2021
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