Related workshops
https://sites.google.com/site/software4ml
https://sites.google.com/site/admlworkshop
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[1] H Brendan McMahan, Gary Holt, D Sculley, Michael Young, Dietmar Ebner, Julian Grady, Lan Nie, Todd Phillips, Eugene Davydov, Daniel Golovin, Sharat Chikkerur, Dan Liu, Martin Wattenberg, Arnar Mar Hrafnkelsson, Tom Boulos, and Jeremy Kubica. Ad click prediction: a view from the trenches. Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1222–1230, 2013. doi: 10.1145/2487575.2488200.
[2] Chinmay Karande, Aranyak Mehta, and Ramakrishnan Srikant. Optimizing budget constrained spend in search advertising. Proceedings of the sixth ACM international conference on Web search and data mining - WSDM ’13, page 697, 2013. doi: 10.1145/2433396.2433483. URL http://dl. acm.org/citation.cfm?doid=2433396.2433483.
[3] Kc Lee, Ali Jalali, and Ali Dasdan. Real Time Bid Optimization with Smooth Budget Delivery in Online Advertising. arXiv preprint arXiv:1305.3011, pages 1–13, 2013. doi: 10.1145/2501040. 2501979. URL http://arxiv.org/abs/1305.3011.
[4] Gagan Aggarwal, S Muthukrishnan, David Pal, and Martin Pal. General Auction Mechanism for Search Advertising. Update, pages 1–20, 2008. ISSN 08963207. doi: 10.1145/1526709.1526742. URL http://arxiv.org/abs/0807.1297.
[5] M. Bumin Yenmez. Pricing in position auctions and online advertising. Economic Theory, 55(1): 243–256, 2014. ISSN 09382259. doi: 10.1007/s00199-013-0748-0.
[6] Wei Li, Xuerui Wang, Ruofei Zhang, Ying Cui, Jianchang Mao, and Rong Jin. Exploitation and exploration in a performance based contextual advertising system. URL http://dl.acm.org/citation.cfm?id= 1835811.
[7] Ying Cui, Ruofei Zhang, Wei Li, and Jianchang Mao. Bid landscape forecasting in online ad exchange marketplace. Proceedings of the 17th ACM SIGKDD international conference on Knowledge discov- ery and data mining - KDD ’11, page 265, 2011. ISSN 1450307574. doi: 10.1145/2020408.2020454. URL http://dl.acm.org/citation.cfm?id=2020408.2020454.
[8] Olivier Chapelle. Modeling delayed feedback in display advertising. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1097–1105. ACM, 2014.
[9] Ralph Breuer and Malte Brettel. Short- and Long-term Effects of Online Advertising: Differences between New and Existing Customers. Journal of Interactive Marketing, 26(3):155–166, 2012. ISSN 10949968. doi: 10.1016/j.intmar.2011.12.001.
[10] Alekh Agarwal, Oliveier Chapelle, Miroslav Dud ́ık, and John Langford. A Reliable Effective Teras- cale Linear Learning System. Journal of Machine Learning Research, 15:1111–1133, 2014. URL http://jmlr.org/papers/v15/agarwal14a.html.
[11] Jeffrey Dean, Greg S Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V Le, Mark Z Mao, Marc Aurelio Ranzato, Andrew Senior, Paul Tucker, Ke Yang, and Andrew Y Ng. Large Scale Distributed Deep Networks. NIPS 2012: Neural Information Processing Systems, pages 1–11, 2012. ISSN 10495258. doi: 10.1109/ICDAR.2011.95.
[12] Matei Zaharia, Mosharaf Chowdhury, Michael J Franklin, Scott Shenker, and Ion Stoica. Spark : Cluster Computing with Working Sets. In HotCloud’10 Proceedings of the 2nd USENIX conference on Hot topics in cloud computing, page 10, 2010. doi: 10.1007/s00256-009-0861-0.
[13] Mu Li, David G Andersen, Jun Woo Park, Alexander J Smola, Amr Ahmed, Vanja Josifovski, James Long, Eugene J Shekita, and Bor-Yiing Su. Scaling distributed machine learning with the parameter server. In 11th USENIX Symposium on Operating Systems Design and Implementation (OSDI 14), pages 583–598, 2014.
[14] Martın Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al. Tensorflow: Large-scale machine learning on heterogeneous systems, 2015. Software available from tensorflow. org.
[15] Lionel C. Briand. Novel Applications of Machine Learning in Software Testing. In 2008 The Eighth International Conference on Quality Software, pages 3–10, 2008. ISBN 978-0-7695-3312-4. doi: 10.1109/QSIC.2008.29. URL http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm? arnumber=4601522.
[16] D. Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Vinay Chaudhary, Michael Young, and Dietmar Ebner. Machine Learning: The high interest credit card of technical depth. In NIPS, 2014.