Sparse low-degree Fourier spectra allow flat minima in transformers for boolean functions up to context-length sparsity, enabling non-vacuous PAC-Bayes generalization bounds via an idealized low-sharpness learner.
On the optimization and generalization of multi-head attention.Transactions on Machine Learning Research, 2023
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A Sharper Picture of Generalization in Transformers
Sparse low-degree Fourier spectra allow flat minima in transformers for boolean functions up to context-length sparsity, enabling non-vacuous PAC-Bayes generalization bounds via an idealized low-sharpness learner.