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cs.LG2023★ 1 cited
Efficient Model Adaptation for Continual Learning at the Edge
Zachary A. Daniels, Jun Hu, Michael Lomnitz +5
Most machine learning (ML) systems assume stationary and matching data distributions during training and deployment. This is often a false assumption. When ML models are deployed o…
cs.LG2023
Experimental observation on a low-rank tensor model for eigenvalue problems
Jun Hu, Pengzhan Jin
Here we utilize a low-rank tensor model (LTM) as a function approximator, combined with the gradient descent method, to solve eigenvalue problems including the Laplacian operator a…