Fetching the paper…
Reading the bibliography…
Click-through rate (CTR) prediction plays a critical role in recommender systems and online advertising.
Predicting clicks: estimating the click-through rate for new ads. In Proceedings of the 16th international conference on World Wide Web . ACM, 521–530
Matthew Richardson, Ewa Dominowska, and Robert Ragno. 2007 · 2007
Earlier work this paper cites.
Matrix factorization techniques for recommender systems
Yehuda Koren, Robert Bell, and Chris Volinsky. 2009 · 2009
Earlier work this paper cites.
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 · 2010
Earlier work this paper cites.
Factorization machines. In Data Mining (ICDM), 2010 IEEE 10th International Conference on . IEEE, 995–1000
Steffen Rendle. 2010 · 2010
Earlier work this paper cites.
Optimal Reserve Prices in Weighted GSP Auctions: Theory and Experimental Methodology. In 7th Ad Auction Workshop in conjunction with the 12th ACM Conference on Electronic Commerce
Sun Yang, Zhou Yunhong, and Deng Xiaotie. 2011 · 2011
Earlier work this paper cites.
Factorization machines with libfm
Steffen Rendle. 2012 · 2012
Earlier work this paper cites.
On the convergence and robustness of reserve pricing in keyword auctions. In Proceedings of the 14th Annual International Conference on Electronic Commerce . 113–120
Yang Sun, Yunhong Zhou, Ming Yin, and Xiaotie Deng. 2012 · 2012
Earlier work this paper cites.
OFF-set: one-pass factorization of feature sets for online recommendation in persistent cold start settings. In Proceedings of the 7th ACM Conference on Recommender Systems . ACM, 375–378
Michal Aharon, Natalie Aizenberg, Edward Bortnikov, Ronny Lempel, Roi Adadi, Tomer Benyamini, Liron Levin, Ran Roth, and Ohad Serfaty. 2013 · 2013
Earlier work this paper cites.
Ad click prediction: a view from the trenches. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining . ACM, 1222–1230
H Brendan McMahan, Gary Holt, David Sculley, Michael Young, Dietmar Ebner, Julian Grady, Lan Nie, Todd Phillips, Eugene Davydov, Daniel Golovin, et al · 2013
Earlier work this paper cites.
Display Advertising Challenge
Criteo Labs. 2014 · 2014
Cited alongside, same era.
Simple and scalable response prediction for display advertising
Olivier Chapelle, Eren Manavoglu, and Romer Rosales. 2015 · 2015
Cited alongside, same era.
Wide & deep learning for recommender systems. In Proceedings of the 1st Workshop on Deep Learning for Recommender Systems . ACM, 7–10
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, et al · 2016
Cited alongside, same era.
Field-aware factorization machines for CTR prediction. In Proceedings of the 10th ACM Conference on Recommender Systems . ACM, 43–50
Yuchin Juan, Yong Zhuang, Wei-Sheng Chin, and Chih-Jen Lin. 2016 · 2016
Cited alongside, same era.
Product-based neural networks for user response prediction. In 2016 IEEE 16th International Conference on Data Mining (ICDM) . IEEE, 1149–1154
Yanru Qu, Han Cai, Kan Ren, Weinan Zhang, Yong Yu, Ying Wen, and Jun Wang. 2016 · 2016
Cited alongside, same era.
Neural Factorization Machines for Sparse Predictive Analytics
Xiangnan He and Tat-Seng Chua. 2017 · 2017
Later among the works it cites.
Field-aware factorization machines in a real-world online advertising system. In Proceedings of the 26th International Conference on World Wide Web Companion . International World Wide Web Conferences Steering Committee, 680–688
Yuchin Juan, Damien Lefortier, and Olivier Chapelle. 2017 · 2017
Later among the works it cites.
Deep & Cross Network for Ad Click Predictions
Ruoxi Wang, Bin Fu, Gang Fu, and Mingliang Wang. 2017 · 2017
Later among the works it cites.
xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems
Jianxun Lian, Xiaohuan Zhou, Fuzheng Zhang, Zhongxia Chen, Xing Xie, and Guangzhong Sun. 2018 · 2018
Later among the works it cites.
Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Deep Crossing: Web-scale modeling without manually crafted combinatorial features. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . ACM, 255–262
Ying Shan, T Ryan Hoens, Jian Jiao, Haijing Wang, Dong Yu, and JC Mao. 2016 · 2016
Cited alongside, same era.
Deep learning over multi-field categorical data. In European conference on information retrieval . Springer, 45–57
Weinan Zhang, Tianming Du, and Jun Wang. 2016 · 2016
Cited alongside, same era.
Pricing ad slots with consecutive multi-unit demand
Xiaotie Deng, Paul Goldberg, Yang Sun, Bo Tang, and Jinshan Zhang. 2017 · 2017
Cited alongside, same era.
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, and Xiuqiang He. 2017 · 2017
Cited alongside, same era.
Rocket launching: A universal and efficient framework for training well-performing light net. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 32
Guorui Zhou, Ying Fan, Runpeng Cui, Weijie Bian, Xiaoqiang Zhu, and Kun Gai. 2018a
Cited in the paper.
Deep interest network for click-through rate prediction. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 1059–1068
Guorui Zhou, Xiaoqiang Zhu, Chenru Song, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, and Kun Gai. 2018b
Cited in the paper.
Junwei Pan, Jian Xu, Alfonso Lobos Ruiz, Wenliang Zhao, Shengjun Pan, Yu Sun, and Quan Lu. 2018 · 2018
Later among the works it cites.
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, and Jian Tang. 2018 · 2018
Later among the works it cites.
Predicting different types of conversions with multi-task learning in online advertising. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 2689–2697
Junwei Pan, Yizhi Mao, Alfonso Lobos Ruiz, Yu Sun, and Aaron Flores. 2019 · 2019
Later among the works it cites.
DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving
Wei Deng, Junwei Pan, Tian Zhou, Aaron Flores, and Guang Lin. 2020 · 2020
Later among the works it cites.