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Papers
Learning Expressive Random Feature Models via Parametrized Activations
UAI 2026
Adversarial Training in High-Dimensional Regression: Generated Data and Neural Networks
AISTATS 2025
Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra
ICLR 2025
How Gradient descent balances features: A dynamical analysis for two-layer neural networks
ICLR 2025
Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations
COLT 2024
Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
ICML 2024
Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs
ICML 2024
On the Sample Complexity of Two-Layer Networks: Lipschitz Vs. Element-Wise Lipschitz Activation
ALT 2024
Sampling from the Mean-Field Stationary Distribution
COLT 2024
Simplicity Bias via Global Convergence of Sharpness Minimization
ICML 2024
Convergence of mean-field Langevin dynamics: time-space discretization, stochastic gradient, and variance reduction
NeurIPS 2023
Efficient displacement convex optimization with particle gradient descent
ICML 2023
Entropic Fictitious Play for Mean Field Optimization Problem
JMLR 2023
Fast Convergence in Learning Two-Layer Neural Networks with Separable Data
AAAI 2023
Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization
NeurIPS 2023
Intrinsic dimensionality and generalization properties of the R-norm inductive bias
COLT 2023
AdaLoss: A Computationally-Efficient and Provably Convergent Adaptive Gradient Method
AAAI 2022
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data
COLT 2022
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions
ICML 2022
Neural Networks can Learn Representations with Gradient Descent
COLT 2022
The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks
COLT 2022
Two-layer neural network on infinite dimensional data: global optimization guarantee in the mean-field regime
NeurIPS 2022
A Law of Robustness for Two-Layers Neural Networks
COLT 2021
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network
COLT 2021
A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Partial Differential Equations
COLT 2021