626 citations · 1.5k across the 21 of their papers we have counts for
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cs.AI2020★ 1 cited
Unifying Model Explainability and Robustness via Machine-Checkable Concepts
Vedant Nanda, Till Speicher, John P. Dickerson +2
As deep neural networks (DNNs) get adopted in an ever-increasing number of applications, explainability has emerged as a crucial desideratum for these models. In many real-world ta…
stat.ML2020
Fair Bayesian Optimization
Valerio Perrone, Michele Donini, Muhammad Bilal Zafar +3
Given the increasing importance of machine learning (ML) in our lives, several algorithmic fairness techniques have been proposed to mitigate biases in the outcomes of the ML model…