@inproceedings{8804cb2fb5ff47198b5dd8b17372687f,
title = "A GPU-Accelerated Population Generation, Sorting, and Mutation Kernel for an Optimization-Based Causal Inference Model",
abstract = "We develop a GPU-accelerated machine learning generative adversarial network model that can be used with observational data for the purpose of constructing causal inferences. The theoretical basis of our machine learning model is novel and is conceptualized to be operable and scalable for high performance computing platforms. Our GPU-accelerated code enables large-scale parallelization of the computation within a common and accessible computing environment. This will expand the reach of our model and empower research in new substantive domains while maintaining the underlying theoretical properties.",
keywords = "Causal Inference, Optimization, Subset Selection",
author = "Cho, {Wendy K.Tam} and Yan Liu",
note = "Publisher Copyright: {\textcopyright} 2023 ACM.; 52nd International Conference on Parallel Processing, ICPP 2023 - Workshops Proceedings ; Conference date: 07-08-2023 Through 10-08-2023",
year = "2023",
month = aug,
day = "7",
doi = "10.1145/3605731.3608930",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "167--171",
booktitle = "52nd International Conference on Parallel Processing, ICPP 2023 - Workshops Proceedings",
address = "United States",
}