Zixiang Chen
23 papers · 2020–2025 · 5 venues · across top CS/AI venues
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Research topics
Machine Learning
(21)
Optimization & Theory Β· Machine Learning
(17)
Deep Learning
(10)
Learning Types Β· Machine Learning
(7)
Artificial Intelligence
(5)
Core Methods
(5)
Optimization & Theory Β· Deep Learning
(5)
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Core AI
(3)
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Natural Language Processing
(2)
Reinforcement Learning
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Generation
(2)
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(2)
Keywords
gradient descent
(8)
convolutional neural network
(4)
neural network optimization
(4)
learning theory
(3)
neural network
(3)
representation learning
(3)
stochastic gradient descent
(2)
reinforcement learning
(2)
relu network
(2)
semi-supervised learning
(2)
regret bound
(2)
risk bound
(2)
benign overfitting
(2)
function approximation
(1)
statistical learning theory
(1)
transfer learning
(1)
non-convex optimization
(1)
feature learning
(1)
convergence analysis
(1)
contrastive learning
(1)
Papers
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 ΞΌ Parametrization
ICML 2025
On the Power of Multitask Representation Learning with Gradient Descent
AISTATS 2025
Fast Sampling via Discrete Non-Markov Diffusion Models with Predetermined Transition Time
NeurIPS 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
NeurIPS 2024
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
NeurIPS 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
How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study
ICLR 2023
Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data
NeurIPS 2023
Understanding Train-Validation Split in Meta-Learning with Neural Networks
ICLR 2023
Why Does Sharpness-Aware Minimization Generalize Better Than SGD?
NeurIPS 2023
Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games
ALT 2022
Benign Overfitting in Two-layer Convolutional Neural Networks
NeurIPS 2022
Faster Perturbed Stochastic Gradient Methods for Finding Local Minima
ALT 2022
Self-training Converts Weak Learners to Strong Learners in Mixture Models
AISTATS 2022
Towards Understanding the Mixture-of-Experts Layer in Deep Learning
NeurIPS 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
NeurIPS 2020