Zixiang Chen
23 papers · 2020–2025 · 5 conferences · across top CS/AI conferences
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Conferences
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ICLR (7)
ICML (4)
AISTATS (2)
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Top co-authors
Keywords
gradient descent
(5)
neural network optimization
(4)
neural network
(2)
risk bound
(2)
benign overfitting
(2)
learning theory
(2)
convolutional neural network
(2)
semi-supervised learning
(1)
text generation
(1)
stochastic gradient descent
(1)
machine translation
(1)
sample complexity
(1)
perceptron algorithm
(1)
text-to-image generation
(1)
statistical learning theory
(1)
reinforcement learning
(1)
computational complexity
(1)
loss landscape
(1)
reinforcement learning from human feedback
(1)
nonconvex optimization
(1)
Papers
On the Power of Multitask Representation Learning with Gradient Descent
AISTATS 2025
Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis
ICLR 2025
Global Convergence and Rich Feature Learning in $L$-Layer Infinite-Width Neural Networks under $μ$ Parametrization
ICML 2025
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
ICML 2024
Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation
NIPS 2024
Fast Sampling via Discrete Non-Markov Diffusion Models with Predetermined Transition Time
NIPS 2024
How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?
ICLR 2024
Matching the Statistical Query Lower Bound for $k$-Sparse Parity Problems with Sign Stochastic Gradient Descent
NIPS 2024
Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP
ICLR 2024
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
ICLR 2023
Benign Overfitting in Two-layer ReLU Convolutional Neural Networks
ICML 2023
Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron
ICML 2023
Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data
NIPS 2023
Why Does Sharpness-Aware Minimization Generalize Better Than SGD?
NIPS 2023
How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study
ICLR 2023
Understanding Train-Validation Split in Meta-Learning with Neural Networks
ICLR 2023
Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games
ALT 2022
Towards Understanding the Mixture-of-Experts Layer in Deep Learning
NIPS 2022
Benign Overfitting in Two-layer Convolutional Neural Networks
NIPS 2022
Self-training Converts Weak Learners to Strong Learners in Mixture Models
AISTATS 2022
Faster Perturbed Stochastic Gradient Methods for Finding Local Minima
ALT 2022
How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?
ICLR 2021
A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks
NIPS 2020