95 citations · 645 across the 72 of their papers we have counts for
19 papers · 1 filter
User-Driven Support for Visualization Prototyping in D3
Hannah K. Bako, Alisha Varma, Anuoluwapo Faboro +5
Templates have emerged as an effective approach to simplifying the visualization design and programming process. For example, they enable users to quickly generate multiple visuali…
Do Invariances in Deep Neural Networks Align with Human Perception?
Vedant Nanda, Ayan Majumdar, Camila Kolling +4
An evaluation criterion for safe and trustworthy deep learning is how well the invariances captured by representations of deep neural networks (DNNs) are shared with humans. We ide…
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization
Mucong Ding, Kezhi Kong, Jingling Li +4
Most state-of-the-art Graph Neural Networks (GNNs) can be defined as a form of graph convolution which can be realized by message passing between direct neighbors or beyond. To sca…
Comparing Human and Machine Bias in Face Recognition
Samuel Dooley, Ryan Downing, George Wei +10
Much recent research has uncovered and discussed serious concerns of bias in facial analysis technologies, finding performance disparities between groups of people based on perceiv…
Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling
Naveen Raman, Sanket Shah, John Dickerson
Rideshare and ride-pooling platforms use artificial intelligence-based matching algorithms to pair riders and drivers. However, these platforms can induce inequality either through…
Robustness Disparities in Commercial Face Detection
Samuel Dooley, Tom Goldstein, John P. Dickerson
Facial detection and analysis systems have been deployed by large companies and critiqued by scholars and activists for the past decade. Critiques that focus on system performance…