Zhenyu Liao

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 28

Top Topics

High Dimensional Data

Kernel Regression

Alternative Clusterings

Top Venues

Publications

Lingyu Gu, Yongqi Du, Yuan Zhang, Di Xie, Shiliang Pu, Robert C. Qiu, Zhenyu Liao
"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach. CoRR (2024)
Hafiz Tiomoko Ali, Zhenyu Liao, Romain Couillet
Random matrices in service of ML footprint: ternary random features with no performance loss. ICLR (2022)
Hafiz Tiomoko Ali, Zhenyu Liao, Romain Couillet
Random matrices in service of ML footprint: ternary random features with no performance loss. CoRR (2021)
Michal Derezinski, Zhenyu Liao, Edgar Dobriban, Michael W. Mahoney
Sparse sketches with small inversion bias. COLT (2021)
Zhenyu Liao, Michael W. Mahoney
Hessian Eigenspectra of More Realistic Nonlinear Models. CoRR (2021)
Zhenyu Liao, Michael W. Mahoney
Hessian Eigenspectra of More Realistic Nonlinear Models. NeurIPS (2021)
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
Sparse Quantized Spectral Clustering. ICLR (2021)
Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens
Kernel regression in high dimensions: Refined analysis beyond double descent. AISTATS (2021)
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent. CoRR (2020)
Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens
Kernel regression in high dimension: Refined analysis beyond double descent. CoRR (2020)
Michal Derezinski, Feynman T. Liang, Zhenyu Liao, Michael W. Mahoney
Precise expressions for random projections: Low-rank approximation and randomized Newton. CoRR (2020)
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
Sparse Quantized Spectral Clustering. CoRR (2020)
Michal Derezinski, Zhenyu Liao, Edgar Dobriban, Michael W. Mahoney
Sparse sketches with small inversion bias. CoRR (2020)
Michal Derezinski, Feynman T. Liang, Zhenyu Liao, Michael W. Mahoney
Precise expressions for random projections: Low-rank approximation and randomized Newton. NeurIPS (2020)
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent. NeurIPS (2020)
Zhenyu Liao, Romain Couillet
On Inner-Product Kernels of High Dimensional Data. CAMSAP (2019)
Xiaoyi Mai, Zhenyu Liao, Romain Couillet
A Large Scale Analysis of Logistic Regression: Asymptotic Performance and New Insights. ICASSP (2019)
Zhenyu Liao, Romain Couillet
A Large Dimensional Analysis of Least Squares Support Vector Machines. IEEE Trans. Signal Process. 67 (4) (2019)
Zhenyu Liao, Romain Couillet
Inner-product Kernels are Asymptotically Equivalent to Binary Discrete Kernels. CoRR (2019)
Xiaoyi Mai, Zhenyu Liao
High Dimensional Classification via Empirical Risk Minimization: Improvements and Optimality. CoRR (2019)
Zhenyu Liao, Romain Couillet
On the Spectrum of Random Features Maps of High Dimensional Data. ICML (2018)
Zhenyu Liao, Romain Couillet
On the Spectrum of Random Features Maps of High Dimensional Data. CoRR (2018)
Zhenyu Liao, Romain Couillet
The Dynamics of Learning: A Random Matrix Approach. ICML (2018)
Zhenyu Liao, Romain Couillet
The Dynamics of Learning: A Random Matrix Approach. CoRR (2018)
Yacine Chitour, Zhenyu Liao, Romain Couillet
A Geometric Approach of Gradient Descent Algorithms in Neural Networks. CoRR (2018)
Romain Couillet, Zhenyu Liao, Xiaoyi Mai
Classification Asymptotics in the Random Matrix Regime. EUSIPCO (2018)
Cosme Louart, Zhenyu Liao, Romain Couillet
A Random Matrix Approach to Neural Networks. CoRR (2017)
Zhenyu Liao, Romain Couillet
Random matrices meet machine learning: A large dimensional analysis of LS-SVM. ICASSP (2017)