arXiv Machine Learning By Karl Pierce, Yuehaw Khoo, Haizhao Yang

Accelerated Learning of High Dimensional Functions with a Tensor-Featured Training Network

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arXiv:2608. 10351v1 Announce Type: new Abstract: In this work we present a method to accelerate the optimization of learning high dimensional functions using deep neural network (DNN).

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arXiv AI
Sep 15

Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks

The paper discusses tensorizing neural networks by reshaping dense weight matrices into higher-order tensors and approximating them with low-rank tensor network decompositions. This approach offers promising model compression and introduces bond indices that create new latent spaces, potentially enhancing interpretability. Despite encouraging empirical results, tensorized neural networks remain underused, and the authors call for more research to address practical scaling and adoption challenges.

By Safa Hamreras, Sukhbinder Singh, Rom\'an Or\'us