430 citations · 869 across the 10 of their papers we have counts for
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stat.ML2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Yaniv Ovadia, Emily Fertig, Jie Ren +6
Modern machine learning methods including deep learning have achieved great success in predictive accuracy for supervised learning tasks, but may still fall short in giving useful…
stat.ML2017★ 177 cited
No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World
Shreya Shankar, Yoni Halpern, Eric Breck +3
Modern machine learning systems such as image classifiers rely heavily on large scale data sets for training. Such data sets are costly to create, thus in practice a small number o…