UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction - researchr publication authors

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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]

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