D. Sculley
D. Sculley
Verified email at google.com - Homepage
Cited by
Cited by
Web-scale k-means clustering
D Sculley
Proceedings of the 19th international conference on World wide web, 1177-1178, 2010
Ad click prediction: a view from the trenches
HB McMahan, G Holt, D Sculley, M Young, D Ebner, J Grady, L Nie, ...
Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013
Hidden technical debt in machine learning systems
D Sculley, G Holt, D Golovin, E Davydov, T Phillips, D Ebner, ...
Advances in neural information processing systems 28, 2503-2511, 2015
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift
Y Ovadia, E Fertig, J Ren, Z Nado, D Sculley, S Nowozin, JV Dillon, ...
arXiv preprint arXiv:1906.02530, 2019
Google vizier: A service for black-box optimization
D Golovin, B Solnik, S Moitra, G Kochanski, J Karro, D Sculley
Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017
Relaxed online SVMs for spam filtering
D Sculley, GM Wachman
Proceedings of the 30th annual international ACM SIGIR conference on …, 2007
Machine learning: The high interest credit card of technical debt
D Sculley, G Holt, D Golovin, E Davydov, T Phillips, D Ebner, ...
Combined regression and ranking
D Sculley
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
Underspecification presents challenges for credibility in modern machine learning
A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...
arXiv preprint arXiv:2011.03395, 2020
Large scale learning to rank
D Sculley
Online active learning methods for fast label-efficient spam filtering.
D Sculley
CEAS 7, 143, 2007
Rank aggregation for similar items
D Sculley
Proceedings of the 2007 SIAM international conference on data mining, 587-592, 2007
Predicting bounce rates in sponsored search advertisements
D Sculley, RG Malkin, S Basu, RJ Bayardo
Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009
Compression and machine learning: A new perspective on feature space vectors
D Sculley, CE Brodley
Data Compression Conference (DCC'06), 332-341, 2006
Winner's curse? On pace, progress, and empirical rigor
D Sculley, J Snoek, A Wiltschko, A Rahimi
No classification without representation: Assessing geodiversity issues in open data sets for the developing world
S Shankar, Y Halpern, E Breck, J Atwood, J Wilson, D Sculley
arXiv preprint arXiv:1711.08536, 2017
Direct-manipulation visualization of deep networks
D Smilkov, S Carter, D Sculley, FB Viégas, M Wattenberg
arXiv preprint arXiv:1708.03788, 2017
The ML test score: A rubric for ML production readiness and technical debt reduction
E Breck, S Cai, E Nielsen, M Salib, D Sculley
2017 IEEE International Conference on Big Data (Big Data), 1123-1132, 2017
Tensorflow. js: Machine learning for the web and beyond
D Smilkov, N Thorat, Y Assogba, A Yuan, N Kreeger, P Yu, K Zhang, ...
arXiv preprint arXiv:1901.05350, 2019
Detecting adversarial advertisements in the wild
D Sculley, ME Otey, M Pohl, B Spitznagel, J Hainsworth, Y Zhou
Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011
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