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Zhenyu Liao
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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