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Feature engineering has been the key to the success of many prediction models.
Principles of mathematical analysis
Walter Rudin and others. 1964 · 1964
Earlier work this paper cites.
Factorization machines. In 2010 IEEE International Conference on Data Mining
Steffen Rendle. 2010 · 2010
Earlier work this paper cites.
Sibyl: A system for large scale supervised machine learning
K. Canini. 2012 · 2012
Earlier work this paper cites.
Factorization Machines with libFM
Steffen Rendle. 2012 · 2012
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Learning polynomials with neural networks
Gregory Valiant. 2014 · 2014
Earlier work this paper cites.
Simple and scalable response prediction for display advertising
Olivier Chapelle, Eren Manavoglu, and Romer Rosales. 2015 · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2015 · 2015
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy. 2015 · 2015
Cited alongside, same era.
Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015 · 2015
Cited alongside, same era.
Deep learning in neural networks: An overview
Jürgen Schmidhuber. 2015 · 2015
Cited alongside, same era.
Tensor machines for learning target-specific polynomial features
Higher-Order Factorization Machines. In Advances in Neural Information Processing Systems
Mathieu Blondel, Akinori Fujino, Naonori Ueda, and Masakazu Ishihata. 2016 · 2016
Later among the works it cites.
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, and others. 2016 · 2016
Later among the works it cites.
Field-aware factorization machines for CTR prediction. In Proceedings of the 10th ACM Conference on Recommender Systems
Yuchin Juan, Yong Zhuang, Wei-Sheng Chin, and Chih-Jen Lin. 2016 · 2016
Later among the works it cites.
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
Ying Shan, T Ryan Hoens, Jian Jiao, Haijing Wang, Dong Yu, and JC Mao. 2016 · 2016
Later among the works it cites.
Residual Networks Behave Like Ensembles of Relatively Shallow Networks
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Jiyan Yang and Alex Gittens. 2015 · 2015
Cited alongside, same era.
Andreas Veit, Michael J Wilber, and Serge Belongie. 2016 · 2016
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
Yuchin Juan, Damien Lefortier, and Olivier Chapelle. 2017 · 2017
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