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Hessian Eigenspectra of More Realistic Nonlinear Models


Mar 17, 2021
Zhenyu Liao, Michael W. Mahoney

* Identical to v1, except for the inclusion of some additional references 

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Sparse sketches with small inversion bias


Nov 21, 2020
MichaƂ DereziƄski, Zhenyu Liao, Edgar Dobriban, Michael W. Mahoney


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Kernel regression in high dimension: Refined analysis beyond double descent


Oct 06, 2020
Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens

* 30 pages, 13 figures 

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Sparse Quantized Spectral Clustering


Oct 03, 2020
Zhenyu Liao, Romain Couillet, Michael W. Mahoney


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Precise expressions for random projections: Low-rank approximation and randomized Newton


Jun 18, 2020
MichaƂ DereziƄski, Feynman Liang, Zhenyu Liao, Michael W. Mahoney


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A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent


Jun 09, 2020
Zhenyu Liao, Romain Couillet, Michael W. Mahoney


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Towards Efficient Training for Neural Network Quantization


Dec 21, 2019
Qing Jin, Linjie Yang, Zhenyu Liao

* 23 pages, 8 figures 

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AdaBits: Neural Network Quantization with Adaptive Bit-Widths


Dec 20, 2019
Qing Jin, Linjie Yang, Zhenyu Liao

* 10 pages, 6 figures, submitted to CVPR 2020 

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Inner-product Kernels are Asymptotically Equivalent to Binary Discrete Kernels


Sep 15, 2019
Zhenyu Liao, Romain Couillet


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Complete Dictionary Learning via $\ell^4$-Norm Maximization over the Orthogonal Group


Jul 10, 2019
Yuexiang Zhai, Zitong Yang, Zhenyu Liao, John Wright, Yi Ma


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High Dimensional Classification via Empirical Risk Minimization: Improvements and Optimality


May 31, 2019
Xiaoyi Mai, Zhenyu Liao


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Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses


Apr 01, 2019
Yingwei Li, Song Bai, Cihang Xie, Zhenyu Liao, Xiaohui Shen, Alan L. Yuille

* The code is available here: https://github.com/LiYingwei/Regional-Homogeneity 

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A Geometric Approach of Gradient Descent Algorithms in Neural Networks


Nov 08, 2018
Yacine Chitour, Zhenyu Liao, Romain Couillet

* Preprint. Work in progress 

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On the Spectrum of Random Features Maps of High Dimensional Data


Jul 20, 2018
Zhenyu Liao, Romain Couillet

* 13 pages (with Supplementary Material), 10 figure, ICML 2018 

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The Dynamics of Learning: A Random Matrix Approach


Jul 20, 2018
Zhenyu Liao, Romain Couillet

* 14 pages (with Supplementary Material), 7 figures, ICML 2018 

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A Random Matrix Approach to Neural Networks


Jun 29, 2017
Cosme Louart, Zhenyu Liao, Romain Couillet


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A Large Dimensional Analysis of Least Squares Support Vector Machines


Jan 11, 2017
Zhenyu Liao, Romain Couillet

* 26 pages, 10 figures, 1 table, partially presented at ICASSP 2017 

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Random matrices meet machine learning: a large dimensional analysis of LS-SVM


Sep 08, 2016
Zhenyu Liao, Romain Couillet

* wrong article submitted 

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Spectral Sparsification and Regret Minimization Beyond Matrix Multiplicative Updates


Jun 16, 2015
Zeyuan Allen-Zhu, Zhenyu Liao, Lorenzo Orecchia


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