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cs.LG2024
Tight and Efficient Upper Bound on Spectral Norm of Convolutional Layers
Ekaterina Grishina, Mikhail Gorbunov, Maxim Rakhuba
Controlling the spectral norm of the Jacobian matrix, which is related to the convolution operation, has been shown to improve generalization, training stability and robustness in…
cs.LG2024
Group and Shuffle: Efficient Structured Orthogonal Parametrization
Mikhail Gorbunov, Nikolay Yudin, Vera Soboleva +3
The increasing size of neural networks has led to a growing demand for methods of efficient fine-tuning. Recently, an orthogonal fine-tuning paradigm was introduced that uses ortho…
math.ST2024
Dimension-free Structured Covariance Estimation
Nikita Puchkin, Maxim Rakhuba
Given a sample of i.i.d. high-dimensional centered random vectors, we consider a problem of estimation of their covariance matrix with an additional assumption that can be…