Scalable hands-free transfer learning for online advertising
By Brian M. D’Alessandro, Daizhuo Chen, Troy Raeder, Claudia Perlich, Melinda Han Williams, Foster J. Provost. 2014
44 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- D. Golovin
- David Sculley
- Michael Young
- Frank Hutter
- Xiaojin Zhu
- Quoc V. Le
- Douwe Kiela
- L. Eon Bottou
In Information Systems
In Management Science and Operations Research
- D. Golovin
- David Sculley
- Michael Young
- Andreas Krause
- Jean-Daniel Zucker
- Yann Chevaleyre
- Nataliya Sokolovska
Citations in the corpus
- Hidden Technical Debt in Machine Learning Systems (2015, background): “Most of the use cases described in this paper have talked about the cost of maintaining a single model, but mature systems may have dozens or hundreds of models running simultaneously [14, 6].”
- Serving DNNs like Clockwork: Performance Predictability from the Bottom Up (2020, background): “The meteoric rise of applications driven by machine learning (ML), ranging from computer vision [20, 66] to ad-targeting [3, 12] to virtual assistants [8,54], has prompted significant interest into making both ML training and inference faster.”