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cs.LG2023
Sample based Explanations via Generalized Representers
Che-Ping Tsai, Chih-Kuan Yeh, Pradeep Ravikumar
We propose a general class of sample based explanations of machine learning models, which we term generalized representers. To measure the effect of a training sample on a model's…
cs.LG2023★ 3 cited
Representer Point Selection for Explaining Regularized High-dimensional Models
Che-Ping Tsai, Jiong Zhang, Eli Chien +3
We introduce a novel class of sample-based explanations we term high-dimensional representers, that can be used to explain the predictions of a regularized high-dimensional model i…