Zhenyu Liao
17 papers · 2018–2025 · 9 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (32)
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Century Club · Bronze
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Prolific Year · Productive
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Keyword Collector
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Research topics
Machine Learning
(15)
Mathematics & Optimization
(10)
Optimization & Theory · Machine Learning
(9)
Core Methods
(8)
Mathematics
(8)
Deep Learning
(5)
Optimization
(5)
Application Areas
(4)
Architectures
(4)
Artificial Intelligence
(2)
Core AI
(2)
Optimization & Theory · Deep Learning
(2)
Computer Science
(1)
Data Science & Analytics
(1)
Foundations
(1)
Keywords
spectral analysis
(4)
random matrix theory
(4)
random matrix
(3)
kernel methods
(3)
model compression
(2)
high-dimensional analysis
(2)
double descent
(2)
inversion bia
(2)
phase transition
(2)
matrix sketching
(2)
random feature
(2)
gaussian mixture model
(2)
numerical optimization
(1)
efficient computing
(1)
incremental learning
(1)
sparse representation
(1)
neural tangent kernel
(1)
statistical learning theory
(1)
gradient descent
(1)
matrix factorization
(1)
Papers
ECC-SNN: Cost-Effective Edge-Cloud Collaboration for Spiking Neural Networks
IJCAI 2025
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton
ICML 2025
The Breakdown of Gaussian Universality in Classification of High-dimensional Linear Factor Mixtures
ICLR 2025
Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures
ICML 2024
"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach
NeurIPS 2022
Random matrices in service of ML footprint: ternary random features with no performance loss
ICLR 2022
Hessian Eigenspectra of More Realistic Nonlinear Models
NeurIPS 2021
Kernel regression in high dimensions: Refined analysis beyond double descent
AISTATS 2021
Sparse Quantized Spectral Clustering
ICLR 2021
Sparse sketches with small inversion bias
COLT 2021
AdaBits: Neural Network Quantization With Adaptive Bit-Widths
CVPR 2020
A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent
NeurIPS 2020
Complete Dictionary Learning via L4-Norm Maximization over the Orthogonal Group
JMLR 2020
Precise expressions for random projections: Low-rank approximation and randomized Newton
NeurIPS 2020
Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses
ECCV 2020
On the Spectrum of Random Features Maps of High Dimensional Data
ICML 2018
The Dynamics of Learning: A Random Matrix Approach
ICML 2018