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papersTODAY 04:00 UTC

Paper reviews tensorization for neural network compression and interpretability

A revised arXiv paper examines tensorization, a method that reshapes a network's dense weight matrices into higher-order tensors and approximates them with low-rank tensor network decompositions. The authors argue the approach remains underused despite promising results as a model compression technique, and they highlight its potential for making networks easier to interpret. The submission appears as a replacement cross-list across arXiv's AI and machine learning categories.

arXiv interpretability model-compression neural-network-compression tensor-network-decomposition tensorization

COVERAGE · 2 REPORTS · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.AITensorization is a powerful but underexplored tool for compression and interpretability of neural networks ↗TODAY 04:00 UTC

arXiv cs.LGTensorization is a powerful but underexplored tool for compression and interpretability of neural networks ↗TODAY 04:00 UTC