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Robustness to distribution shift has become a growing concern for text and image models as they transition from research subjects to deployment in the real world.
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A good credit score did not protect latino and black borrowers
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Impact of hba1c measurement on hospital readmission rates: analysis of 70,000 clinical database patient records
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Diversity in clinical and biomedical research: a promise yet to be fulfilled
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Librispeech: an asr corpus based on public domain audio books
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur · 2015
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Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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Why are health studies so white?
Natalie Jacewicz · 2016
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Mimic-iii, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, Li-wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016
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Deep coral: Correlation alignment for deep domain adaptation
Baochen Sun and Kate Saenko · 2016
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Centers for Disease Control and Prevention (CDC) · 2017
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Audio set: An ontology and human-labeled dataset for audio events
Jort F Gemmeke, Daniel PW Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R Channing Moore, Manoj Plakal, and Marvin Ritter · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Development and validation of qdiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study
Julia Hippisley-Cox and Carol Coupland · 2017
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Lightgbm: A highly efficient gradient boosting decision tree
Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, and Tie-Yan Liu · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Economic costs of diabetes in the us in 2017
American Diabetes Association · 2018
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Catboost: gradient boosting with categorical features support
Anna Veronika Dorogush, Vasily Ershov, and Andrey Gulin · 2018
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Clinical trials have far too little racial and ethnic diversity
Scientific American Editors · 2018
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Domain generalization with adversarial feature learning
Haoliang Li, Sinno Jialin Pan, Shiqi Wang, and Alex C Kot · 2018
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Health-care utilization as a proxy in disability determination
National Academies of Sciences Engineering, Medicine, et al · 2018
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Benchmarking deep learning models on large healthcare datasets
Sanjay Purushotham, Chuizheng Meng, Zhengping Che, and Yan Liu · 2018
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Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman · 2018
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Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz · 2019
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Propublica’s compas data revisited
Matias Barenstein · 2019
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Well-tuned simple nets excel on tabular datasets
Arlind Kadra, Marius Lindauer, Frank Hutter, and Josif Grabocka · 2021
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Wilds: A benchmark of in-the-wild distribution shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, et al · 2021
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Out-of-distribution generalization via risk extrapolation (rex)
David Krueger, Ethan Caballero, Joern-Henrik Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Remi Le Priol, and Aaron Courville · 2021
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Are we learning yet? a meta review of evaluation failures across machine learning
Thomas Liao, Rohan Taori, Inioluwa Deborah Raji, and Ludwig Schmidt · 2021
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Accuracy on the line: on the strong correlation between out-of-distribution and in-distribution generalization
John P Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, and Ludwig Schmidt · 2021
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Explaining the black-white homeownership gap
Jung Hyun Choi, Alanna McCargo, Michael Neal, Laurie Goodman, and Caitlin Young · 2019
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A comparative study of fairness-enhancing interventions in machine learning
Sorelle A Friedler, Carlos Scheidegger, Suresh Venkatasubramanian, Sonam Choudhary, Evan P Hamilton, and Derek Roth · 2019
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An open source automl benchmark
Pieter Gijsbers, Erin LeDell, Janek Thomas, Sébastien Poirier, Bernd Bischl, and Joaquin Vanschoren · 2019
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Hrayr Harutyunyan, Hrant Khachatrian, David C Kale, Greg Ver Steeg, and Aram Galstyan · 2019
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Holistic evaluation of language models
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Shifts: A dataset of real distributional shift across multiple large-scale tasks
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Credit health during the covid-19 pandemic
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