Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Lei, Mingxi"'
Deep learning models often struggle with generalization when deploying on real-world data, due to the common distributional shift to the training data. Test-time adaptation (TTA) is an emerging scheme used at inference time to address this issue. In
Externí odkaz:
http://arxiv.org/abs/2412.07980
(Stochastic) bilevel optimization is a frequently encountered problem in machine learning with a wide range of applications such as meta-learning, hyper-parameter optimization, and reinforcement learning. Most of the existing studies on this problem
Externí odkaz:
http://arxiv.org/abs/2210.01063
Publikováno v:
In Neurocomputing 7 February 2025 617
Autor:
Lei, Mingxi, Varghese, Bino, Hwang, Darryl, Cen, Steven, Lei, Xiaomeng, Azadikhah, Afshin, Desai, Bhushan, Oberai, Assad, Duddalwar, Vinay
There is no consensus regarding the radiomic feature terminology, the underlying mathematics, or their implementation. This creates a scenario where features extracted using different toolboxes could not be used to build or validate the same model le
Externí odkaz:
http://arxiv.org/abs/2006.12761
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2021 Nov; Vol. 2021, pp. 616-620.