Representation Learning-Assisted Click-Through Rate Prediction

Predicting clicks: estimating the click-through rate for new ads

Matthew Richardson, Ewa Dominowska, and Robert Ragno · 2007

Earlier work this paper cites.

Matrix factorization techniques for recommender systems

Yehuda Koren, Robert Bell, and Chris Volinsky · 2009

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Learning to rank for information retrieval

Tie-Yan Liu et al · 2009

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Rectified linear units improve restricted boltzmann machines

Vinod Nair and Geoffrey E Hinton · 2010

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Factorization machines

Steffen Rendle · 2010

Earlier work this paper cites.

Adaptive subgradient methods for online learning and stochastic optimization

John Duchi, Elad Hazan, and Yoram Singer · 2011

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Factorization machines with libfm

Steffen Rendle · 2012

Earlier work this paper cites.

Learning deep structured semantic models for web search using clickthrough data

Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, and Larry Heck · 2013

Earlier work this paper cites.

Ad click prediction: a view from the trenches

H Brendan McMahan, Gary Holt, David Sculley, Michael Young, Dietmar Ebner, Julian Grady, Lan Nie, Todd Phillips, Eugene Davydov, Daniel Golovin, et al · 2013

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Distributed representations of words and phrases and their compositionality

Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013

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Deep content-based music recommendation

Aaron Van den Oord, Sander Dieleman, and Benjamin Schrauwen · 2013

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Practical lessons from predicting clicks on ads at facebook

Xinran He, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu, Tao Xu, Yanxin Shi, Antoine Atallah, Ralf Herbrich, Stuart Bowers, et al · 2014

Cited alongside, same era.

Dropout: a simple way to prevent neural networks from overfitting

Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014

Cited alongside, same era.

Simple and scalable response prediction for display advertising

Olivier Chapelle, Eren Manavoglu, and Romer Rosales · 2015

Cited alongside, same era.

Deep learning

Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015

Cited alongside, same era.

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

Cited alongside, same era.

Deep neural networks for youtube recommendations

Paul Covington, Jay Adams, and Emre Sargin · 2016

Deep learning over multi-field categorical data

Weinan Zhang, Tianming Du, and Jun Wang · 2016

Later among the works it cites.

Deepfm: a factorization-machine based neural network for ctr prediction

Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, and Xiuqiang He · 2017

Later among the works it cites.

Neural factorization machines for sparse predictive analytics

Xiangnan He and Tat-Seng Chua · 2017

Later among the works it cites.

Deep & cross network for ad click predictions

Ruoxi Wang, Bin Fu, Gang Fu, and Mingliang Wang · 2017

Later among the works it cites.

Recommendation with multi-source heterogeneous information

Li Gao, Hong Yang, Jia Wu, Chuan Zhou, Weixue Lu, and Yue Hu · 2018

Later among the works it cites.

Improving entity recommendation with search log and multi-task learning

Jizhou Huang, Wei Zhang, Yaming Sun, Haifeng Wang, and Ting Liu · 2018