575 citations · 929 across the 52 of their papers we have counts for
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cs.LG2021
Black-box tests for algorithmic stability
Byol Kim, Rina Foygel Barber
Algorithmic stability is a concept from learning theory that expresses the degree to which changes to the input data (e.g., removal of a single data point) may affect the outputs o…
math.ST2021
Binary classification with corrupted labels
Yonghoon Lee, Rina Foygel Barber
In a binary classification problem where the goal is to fit an accurate predictor, the presence of corrupted labels in the training data set may create an additional challenge. How…
math.ST2021★ 1 cited
Convergence guarantee for the sparse monotone single index model
Ran Dai, Hyebin Song, Rina Foygel Barber +1
We consider a high-dimensional monotone single index model (hdSIM), which is a semiparametric extension of a high-dimensional generalize linear model (hdGLM), where the link functi…