27 citations · 55 across the 11 of their papers we have counts for
5 papers · 1 filter
Efficient Representation of the Activation Space in Deep Neural Networks
Tanya Akumu, Celia Cintas, Girmaw Abebe Tadesse +3
The representations of the activation space of deep neural networks (DNNs) are widely utilized for tasks like natural language processing, anomaly detection and speech recognition.…
Auditing Predictive Models for Intersectional Biases
Kate S. Boxer, Edward McFowland, Daniel B. Neill
Predictive models that satisfy group fairness criteria in aggregate for members of a protected class, but do not guarantee subgroup fairness, could produce biased predictions for i…
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
Neil Menghani, Edward McFowland, Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic…
Provable Detection of Propagating Sampling Bias in Prediction Models
Pavan Ravishankar, Qingyu Mo, Edward McFowland +1
With an increased focus on incorporating fairness in machine learning models, it becomes imperative not only to assess and mitigate bias at each stage of the machine learning pipel…
Subset Scanning Over Neural Network Activations
Skyler Speakman, Srihari Sridharan, Sekou Remy +2
This work views neural networks as data generating systems and applies anomalous pattern detection techniques on that data in order to detect when a network is processing an anomal…