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stat.ML2024
Linear Recursive Feature Machines provably recover low-rank matrices
Adityanarayanan Radhakrishnan, Mikhail Belkin, Dmitriy Drusvyatskiy
A fundamental problem in machine learning is to understand how neural networks make accurate predictions, while seemingly bypassing the curse of dimensionality. A possible explanat…
stat.ML2023★ 3 cited
Mechanism of feature learning in convolutional neural networks
Daniel Beaglehole, Adityanarayanan Radhakrishnan, Parthe Pandit +1
Understanding the mechanism of how convolutional neural networks learn features from image data is a fundamental problem in machine learning and computer vision. In this work, we i…