Yu Wu, Dimitris Spathis, Hong Jia, Ignacio Perez-Pozuelo, Tomas I. Gonzales, Søren Brage, Nicholas J. Wareham, Cecilia Mascolo. UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction. In Kaivalya Deshpande, Madalina Fiterau, Shalmali Joshi, Zachary C. Lipton, Rajesh Ranganath, Iñigo Urteaga, Serene Yeung, editors, Machine Learning for Healthcare Conference, MLHC 2023, 11-12 August 2023, New York, USA. Volume 219 of Proceedings of Machine Learning Research, pages 863-883, PMLR, 2023. [doi]
@inproceedings{WuSJPGBWM23,
title = {UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction},
author = {Yu Wu and Dimitris Spathis and Hong Jia and Ignacio Perez-Pozuelo and Tomas I. Gonzales and Søren Brage and Nicholas J. Wareham and Cecilia Mascolo},
year = {2023},
url = {https://proceedings.mlr.press/v219/wu23a.html},
researchr = {https://researchr.org/publication/WuSJPGBWM23},
cites = {0},
citedby = {0},
pages = {863-883},
booktitle = {Machine Learning for Healthcare Conference, MLHC 2023, 11-12 August 2023, New York, USA},
editor = {Kaivalya Deshpande and Madalina Fiterau and Shalmali Joshi and Zachary C. Lipton and Rajesh Ranganath and Iñigo Urteaga and Serene Yeung},
volume = {219},
series = {Proceedings of Machine Learning Research},
publisher = {PMLR},
}