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News/Gradient Clipping Beyond Vector Norms: A Spectral Approach for Matrix-Valued Parameters
arxiv
PublishedMay 13, 2026 at 4:00 AM

Gradient Clipping Beyond Vector Norms: A Spectral Approach for Matrix-Valued Parameters

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arXiv:2605.11838v1 Announce Type: new Abstract: Gradient clipping is a standard safeguard for training neural networks under noisy, heavy-tailed stochastic gradients; yet, most clipping rules treat all parameters as vectors and ignore the matrix structure of modern architectures. We show empirically

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