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[1]
Cosme Louart, Zhenyu Liao, and Romain Couillet. A Random Matrix Approach to Neural Networks. The Annals of Applied Probability 28(2) (Apr. 2018), 1190–1248.
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[2]
Zhenyu Liao and Romain Couillet. A Large Dimensional Analysis of Least Squares Support Vector Machines. IEEE Transactions on Signal Processing 67(4) (Feb. 2019), 1065–1074.
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[3]
Zhenyu Liao, Romain Couillet, and Michael W Mahoney. A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent. Journal of Statistical Mechanics: Theory and Experiment 2021(12) (Dec. 2021), 124006.
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[4]
Zhenyu Liao and Romain Couillet. On the Spectrum of Random Features Maps of High Dimensional Data. International Conference on Machine Learning (ICML). Vol. 80. PMLR, July, 2018, pp.3063–3071.
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[5]
Zhenyu Liao and Romain Couillet. The Dynamics of Learning: A Random Matrix Approach. International Conference on Machine Learning (ICML). Vol. 80. PMLR, July 2018, pp.3072–3081.
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[6]
Michal Derezinski, Feynman T Liang, Zhenyu Liao, and Michael W. Mahoney. Precise expressions for random projections: Low-rank approximation and randomized Newton. Advances in Neural Information Processing Systems (NeurIPS). Vol. 33. Curran Associates, Inc., 2020, pp.18272–18283.