GLT-PEFT combines Tucker decomposition for tensor low-rank adaptation with Lie group multiplicative updates and a gating mechanism to enable efficient cross-task transfer from segmentation pretraining to AD diagnosis in 3D CNNs.
Boccardi, et al., Training labels for hippocampal segmentation based on the eadc-adni harmonized hippocampal protocol, Alzheimer’s & De- mentia 11 (2) (2015) 175–183
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GLT-PEFT: Gated Lie-Tucker Parameter-Efficient Fine-Tuning for Alzheimer's Disease Diagnosis with Hippocampal Segmentation Pretraining
GLT-PEFT combines Tucker decomposition for tensor low-rank adaptation with Lie group multiplicative updates and a gating mechanism to enable efficient cross-task transfer from segmentation pretraining to AD diagnosis in 3D CNNs.