D. Sculley

According to our database, D. Sculley authored at least 42 papers between 2006 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Adversarial Nibbler: A Data-Centric Challenge for Improving the Safety of Text-to-Image Models.

Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Max Bartolo, Oana Inel, Juan Ciro, Rafael Mosquera, Addison Howard, Will Cukierski, D. Sculley, Vijay Janapa Reddi, Lora Aroyo

CoRR, 2023

DataPerf: Benchmarks for Data-Centric AI Development.

Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Underspecification Presents Challenges for Credibility in Modern Machine Learning.

Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley

J. Mach. Learn. Res., 2022

Plex: Towards Reliability using Pretrained Large Model Extensions.

Dustin Tran, Jeremiah Z. Liu, Michael W. Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, Kelly Buchanan, Kevin Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

CoRR, 2022

2021

Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning.

Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Z. Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran

CoRR, 2021

A Voice-Activated Switch for Persons with Motor and Speech Impairments: Isolated-Vowel Spotting Using Neural Networks.

Shanqing Cai, Lisie Lillianfeld, Katie Seaver, Jordan R. Green, Michael P. Brenner, Philip C. Nelson, D. Sculley

Proceedings of the Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August, 2021

2020

Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift.

Zachary Nado, Shreyas Padhy, D. Sculley, Alexander D'Amour, Balaji Lakshminarayanan, Jasper Snoek

CoRR, 2020

Population-Based Black-Box Optimization for Biological Sequence Design.

Christof Angermüller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy J. Colwell, D. Sculley

Proceedings of the 37th International Conference on Machine Learning, 2020

Fairness is not static: deeper understanding of long term fairness via simulation studies.

Alexander D'Amour, Hansa Srinivasan, James Atwood, Pallavi Baljekar, D. Sculley, Yoni Halpern

Proceedings of the FAT* '20: Conference on Fairness, 2020

2019

Fair treatment allocations in social networks.

James Atwood, Hansa Srinivasan, Yoni Halpern, David Sculley

CoRR, 2019

Avoiding a Tragedy of the Commons in the Peer Review Process.

D. Sculley, Jasper Snoek, Alexander B. Wiltschko

CoRR, 2019

Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift.

Jasper Snoek, Yaniv Ovadia, Emily Fertig, Balaji Lakshminarayanan, Sebastian Nowozin, D. Sculley, Joshua V. Dillon, Jie Ren, Zachary Nado

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

TensorFlow.js: Machine Learning For The Web and Beyond.

Daniel Smilkov, Nikhil Thorat, Yannick Assogba, Ann Yuan, Nick Kreeger, Ping Yu, Kangyi Zhang, Shanqing Cai, Eric Nielsen, David Soergel, Stan Bileschi, Michael Terry, Charles Nicholson, Sandeep N. Gupta, Sarah Sirajuddin, D. Sculley, Rajat Monga, Greg Corrado, Fernanda B. Viégas, Martin Wattenberg

Proceedings of Machine Learning and Systems 2019, 2019

AutoGraph: Imperative-style Coding with Graph-based Performance.

Dan Moldovan, James M. Decker, Fei Wang, Andrew A. Johnson, Brian K. Lee, Zachary Nado, D. Sculley, Tiark Rompf, Alexander B. Wiltschko

Proceedings of Machine Learning and Systems 2019, 2019

2018

BriarPatches: Pixel-Space Interventions for Inducing Demographic Parity.

Alexey A. Gritsenko, Alex D'Amour, James Atwood, Yoni Halpern, D. Sculley

CoRR, 2018

Winner's Curse? On Pace, Progress, and Empirical Rigor.

D. Sculley, Jasper Snoek, Alexander B. Wiltschko, Ali Rahimi

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Direct-Manipulation Visualization of Deep Networks.

Daniel Smilkov, Shan Carter, D. Sculley, Fernanda B. Viégas, Martin Wattenberg

CoRR, 2017

Learning to Count Mosquitoes for the Sterile Insect Technique.

Yaniv Ovadia, Yoni Halpern, Dilip Krishnan, Josh Livni, Daniel E. Newburger, Ryan Poplin, Tiantian Zha, D. Sculley

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Google Vizier: A Service for Black-Box Optimization.

Daniel Golovin, Benjamin Solnik, Subhodeep Moitra, Greg Kochanski, John Karro, D. Sculley

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks.

Heng-Tze Cheng, Zakaria Haque, Lichan Hong, Mustafa Ispir, Clemens Mewald, Illia Polosukhin, Georgios Roumpos, D. Sculley, Jamie Smith, David Soergel, Yuan Tang, Philipp Tucker, Martin Wicke, Cassandra Xia, Jianwei Xie

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

The ML test score: A rubric for ML production readiness and technical debt reduction.

Eric Breck, Shanqing Cai, Eric Nielsen, Michael Salib, D. Sculley

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

AutoMOS: Learning a non-intrusive assessor of naturalness-of-speech.

Brian Patton, Yannis Agiomyrgiannakis, Michael Terry, Kevin W. Wilson, Rif A. Saurous, D. Sculley

CoRR, 2016

2015

Hidden Technical Debt in Machine Learning Systems.

D. Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-François Crespo, Dan Dennison

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2013

Ad click prediction: a view from the trenches.

H. Brendan McMahan, Gary Holt, David 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, 2013

Large-Scale Learning with Less RAM via Randomization.

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

Proceedings of the 30th International Conference on Machine Learning, 2013

2011

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 Knowledge Discovery and Data Mining, 2011

2010

Web-scale k-means clustering.

D. Sculley

Proceedings of the 19th International Conference on World Wide Web, 2010

Combined regression and ranking.

D. Sculley

Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2009

Predicting bounce rates in sponsored search advertisements.

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

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

2008

Meaning and mining: the impact of implicit assumptions in data mining for the humanities.

D. Sculley, Bradley M. Pasanek

Lit. Linguistic Comput., 2008

Mining millions of metaphors.

Bradley M. Pasanek, D. Sculley

Lit. Linguistic Comput., 2008

A Distance-Based Method for Detecting Horizontal Gene Transfer in Whole Genomes.

Xintao Wei, Lenore Cowen, Carla E. Brodley, Arthur Brady, D. Sculley, Donna K. Slonim

Proceedings of the Bioinformatics Research and Applications, 2008

Filtering Email Spam in the Presence of Noisy User Feedback.

D. Sculley, Gordon V. Cormack

Proceedings of the CEAS 2008, 2008

On Free Speech and Civil Discourse: Filtering Abuse in Blog Comments.

D. Sculley

Proceedings of the CEAS 2008, 2008

2007

Relaxed Online SVMs in the TREC Spam Filtering Track.

David Sculley, Gabriel Wachman

Proceedings of The Sixteenth Text REtrieval Conference, 2007

Relaxed online SVMs for spam filtering.

D. Sculley, Gabriel Wachman

Proceedings of the SIGIR 2007: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2007

Rank Aggregation for Similar Items.

D. Sculley

Proceedings of the Seventh SIAM International Conference on Data Mining, 2007

Practical learning from one-sided feedback.

D. Sculley

Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Online Active Learning Methods for Fast Label-Efficient Spam Filtering.

D. Sculley

Proceedings of the CEAS 2007, 2007

2006

Spam Filtering Using Inexact String Matching in Explicit Feature Space with On-Line Linear Classifiers.

David Sculley, Gabriel Wachman, Carla E. Brodley

Proceedings of the Fifteenth Text REtrieval Conference, 2006

Beyond Digital Incunabula: Modeling the Next Generation of Digital Libraries.

Gregory R. Crane, David Bamman, Lisa Cerrato, Alison Jones, David M. Mimno, Adrian Packel, David Sculley, Gabriel Weaver

Proceedings of the Research and Advanced Technology for Digital Libraries, 2006

Compression and Machine Learning: A New Perspective on Feature Space Vectors.

D. Sculley, Carla E. Brodley

Proceedings of the 2006 Data Compression Conference (DCC 2006), 2006