Fanghui Liu
25 papers · 2020–2025 · 7 conferences · across top CS/AI conferences
Achievements
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Conferences
NIPS (8)
ICML (5)
ICLR (4)
JMLR (3)
AAAI (2)
AISTATS (2)
ECCV (1)
Top co-authors
Keywords
neural tangent kernel
(5)
generalization bound
(5)
neural network
(4)
kernel methods
(4)
function approximation
(3)
reproducing kernel hilbert space
(3)
kernel ridge regression
(3)
neural network robustness
(2)
barron space
(2)
double descent
(2)
regret bound
(2)
deep neural network
(2)
random feature
(2)
neural network optimization
(1)
neural architecture search
(1)
self-attention mechanism
(1)
sample complexity
(1)
global convergence
(1)
sample efficiency
(1)
reinforcement learning
(1)
Papers
How Gradient descent balances features: A dynamical analysis for two-layer neural networks
ICLR 2025
LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently
ICML 2025
Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks
JMLR 2024
The Role of Over-Parameterization in Machine Learning β the Good, the Bad, the Ugly
AAAI 2024
Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy
ECCV 2024
Generalization of Scaled Deep ResNets in the Mean-Field Regime
ICLR 2024
Robust NAS under adversarial training: benchmark, theory, and beyond
ICLR 2024
Efficient local linearity regularization to overcome catastrophic overfitting
ICLR 2024
Revisiting Character-level Adversarial Attacks for Language Models
ICML 2024
High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization
ICML 2024
Benign Overfitting in Deep Neural Networks under Lazy Training
ICML 2023
What can online reinforcement learning with function approximation benefit from general coverage conditions?
ICML 2023
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks
NIPS 2023
On the Convergence of Encoder-only Shallow Transformers
NIPS 2023
Sound and Complete Verification of Polynomial Networks
NIPS 2022
Generalization Properties of NAS under Activation and Skip Connection Search
NIPS 2022
Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study
NIPS 2022
On the Double Descent of Random Features Models Trained with SGD
NIPS 2022
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization)
NIPS 2022
Understanding Deep Neural Function Approximation in Reinforcement Learning via $\epsilon$-Greedy Exploration
NIPS 2022
Generalization Properties of hyper-RKHS and its Applications
JMLR 2021
Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures
AISTATS 2021
Kernel regression in high dimensions: Refined analysis beyond double descent
AISTATS 2021
Learning Data-adaptive Non-parametric Kernels
JMLR 2020
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling
AAAI 2020