D. Sculley
D. Sculley
Kaggle & Google
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Cited by
Cited by
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, J Dillon, ...
Advances in neural information processing systems 32, 2019
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, 2015
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
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
Underspecification presents challenges for credibility in modern machine learning
A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...
Journal of Machine Learning Research 23 (226), 1-61, 2022
Machine learning: The high interest credit card of technical debt
D Sculley, G Holt, D Golovin, E Davydov, T Phillips, D Ebner, ...
SE4ML: software engineering for machine learning (NIPS 2014 Workshop) 111, 112, 2014
Relaxed online SVMs for spam filtering
D Sculley, GM Wachman
Proceedings of the 30th annual international ACM SIGIR conference on …, 2007
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
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
Using deep learning to annotate the protein universe
ML Bileschi, D Belanger, DH Bryant, T Sanderson, B Carter, D Sculley, ...
Nature Biotechnology 40 (6), 932-937, 2022
Fairness is not static: deeper understanding of long term fairness via simulation studies
A D'Amour, H Srinivasan, J Atwood, P Baljekar, D Sculley, Y Halpern
Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020
Tensorflow. js: Machine learning for the web and beyond
D Smilkov, N Thorat, Y Assogba, C Nicholson, N Kreeger, P Yu, S Cai, ...
Proceedings of Machine Learning and Systems 1, 309-321, 2019
Evaluating prediction-time batch normalization for robustness under covariate shift
Z Nado, S Padhy, D Sculley, A D'Amour, B Lakshminarayanan, J Snoek
arXiv preprint arXiv:2006.10963, 2020
Combined regression and ranking
D Sculley
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
Winner's curse? On pace, progress, and empirical rigor
D Sculley, J Snoek, A Wiltschko, A Rahimi
Direct-manipulation visualization of deep networks
D Smilkov, S Carter, D Sculley, FB Viégas, M Wattenberg
arXiv preprint arXiv:1708.03788, 2017
Large scale learning to rank
D Sculley
Online active learning methods for fast label-efficient spam filtering.
D Sculley
CEAS 7, 143, 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
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