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cs.LG2024
TL-PCA: Transfer Learning of Principal Component Analysis
Sharon Hendy, Yehuda Dar
Principal component analysis (PCA) can be significantly limited when there is too few examples of the target data of interest. We propose a transfer learning approach to PCA (TL-PC…
cs.LG2024
How Do the Architecture and Optimizer Affect Representation Learning? On the Training Dynamics of Representations in Deep Neural Networks
Yuval Sharon, Yehuda Dar
In this paper, we elucidate how representations in deep neural networks (DNNs) evolve during training. Our focus is on overparameterized learning settings where the training contin…