Eric Breck
I am interested in practical issues in large-scale application of machine learning, including considerations of fairness as well as testing and validation of ML systems.
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The Inclusive Images Competition
D. Sculley
Igor Ivanov
Miha Skalic
Pallavi Baljekar
Pavel Ostyakov
Roman Solovyev
Weimin Wang
Yoni Halpern
Springer Series (2019)
Data Validation for Machine Learning
Marty Zinkevich
Neoklis Polyzotis
Steven Whang
Sudip Roy
Proceedings of SysML (2019) (to appear)
No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World
Shreya Shankar
Yoni Halpern
D. Sculley
NIPS 2017 workshop: Machine Learning for the Developing World
TFX: A TensorFlow-Based Production-Scale Machine Learning Platform
Akshay Naresh Modi
Chiu Yuen Koo
Chuan Yu Foo
Clemens Mewald
Denis M. Baylor
Jarek Wilkiewicz
Levent Koc
Lukasz Lew
Martin A. Zinkevich
Mustafa Ispir
Neoklis Polyzotis
Steven Whang
Sudip Roy
Sukriti Ramesh
Vihan Jain
Xin Zhang
Zakaria Haque
KDD 2017
TensorFlow Debugger: Debugging Dataflow Graphs for Machine Learning
Eric Nielsen
Michael Salib
D. Sculley
Proceedings of the Reliable Machine Learning in the Wild - NIPS 2016 Workshop (2016)
What’s your ML test score? A rubric for ML production systems
Eric Nielsen
Michael Salib
D. Sculley
Reliable Machine Learning in the Wild - NIPS 2016 Workshop (2016)
