D. Sculley

I'm currently interested in massive scale machine learning problems for online advertising. My work includes both novel research and applied engineering.

For more details, see my home page.

Google Publications

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    Machine Learning: The High Interest Credit Card of Technical Debt

    D. Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young

    SE4ML: Software Engineering for Machine Learning (NIPS 2014 Workshop)

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    Ad Click Prediction: a View from the Trenches

    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, Jeremy Kubica

    Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) (2013)

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    Large-Scale Learning with Less RAM via Randomization

    Daniel Golovin, D. Sculley, H. Brendan McMahan, Michael Young

    Proceedings of the 30 International Conference on Machine Learning (ICML) (2013), pp. 10

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    Detecting Adversarial Advertisements in the Wild

    D. Sculley, Matthew Eric Otey, Michael Pohl, Bridget Spitznagel, John Hainsworth, Yunkai Zhou

    Proceedings of the 17th ACM SIGKDD International Conference on Data Mining and Knowledge Discovery, KDD (2011)

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    Going Mini: Extreme Lightweight Spam Filters

    D. Sculley, Gordon V. Cormack

    CEAS 2009: Proceedings of the Sixth Conference on Email and Anti-Spam

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    Large Scale Learning to Rank

    D. Sculley

    NIPS 2009 Workshop on Advances in Ranking

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    Predicting Bounce Rates in Sponsored Search Advertisements

    D. Sculley, Robert Malkin, Sugato Basu, Roberto J. Bayardo

    Proc. of the 15th International ACM-SIGKDD Conference on Knowledge Discovery and Data Mining, ACM (2009), pp. 1325-1334