4 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.HC2022
Trucks Don't Mean Trump: Diagnosing Human Error in Image Analysis
J. D. Zamfirescu-Pereira, Jerry Chen, Emily Wen +3
Algorithms provide powerful tools for detecting and dissecting human bias and error. Here, we develop machine learning methods to to analyze how humans err in a particular high-sta…
cs.CV2021
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation
Soham Gadgil, Mark Endo, Emily Wen +2
Medical image segmentation models are typically supervised by expert annotations at the pixel-level, which can be expensive to acquire. In this work, we propose a method that combi…
cs.LG2020★ 4 cited
How Not to Give a FLOP: Combining Regularization and Pruning for Efficient Inference
Tai Vu, Emily Wen, Roy Nehoran
The challenge of speeding up deep learning models during the deployment phase has been a large, expensive bottleneck in the modern tech industry. In this paper, we examine the use…