A spatio-channel clustering framework for CNN compression reduces FLOPs by 81% and raises brain tumor MRI classification accuracy from 87.76% to 89.80% compared with global SVD and Tucker baselines.
A multilinear singular value decomposition,
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An overview revisits LoRA variants by categorizing advances in architectural design, efficient optimization, and applications while linking them to classical signal processing tools for principled fine-tuning.
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Hierarchical Spatio-Channel Clustering for Efficient Model Compression in Medical Image Analysis
A spatio-channel clustering framework for CNN compression reduces FLOPs by 81% and raises brain tumor MRI classification accuracy from 87.76% to 89.80% compared with global SVD and Tucker baselines.
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Low-Rank Adaptation Redux for Large Models
An overview revisits LoRA variants by categorizing advances in architectural design, efficient optimization, and applications while linking them to classical signal processing tools for principled fine-tuning.