Mutual Information, Compression Bounds, Feature Selection, Rate-Distortion Theory
SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation
arxiv.org·1d
RL-Driven Semantic Compression Model Selection and Resource Allocation in Semantic Communication Systems
arxiv.org·1d
DRIFT: Data Reduction via Informative Feature Transformation- Generalization Begins Before Deep Learning starts
arxiv.org·13h
AMF-MedIT: An Efficient Align-Modulation-Fusion Framework for Medical Image-Tabular Data
arxiv.org·13h
Why Your Next LLM Might Not Have A Tokenizer
towardsdatascience.com·22h
Kernel spectral joint embeddings for high-dimensional noisy datasets using duo-landmark integral operators
arxiv.org·1d
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