← Authors

Zixiang Chen

23 papers · 2020–2025 · 5 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (5) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (28) 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐝 Cross-Pollinator (14) 🌍 Conference Polyglot (5) 🀝 Dynamic Duo (23) πŸ‘‘ Triple Crown πŸ”₯ Unstoppable (6) πŸ’Ž Century Club (23) ⚑ Prolific Year (6) πŸ“ˆ Trend Setter ❓ The Questioner (4) πŸ—ƒοΈ Keyword Collector (65)

Conferences

NIPS (8) ICLR (7) ICML (4) AISTATS (2) ALT (2)

Top co-authors

Quanquan Gu (23) Yiwen Kou (7) Yuan Cao (6) Difan Zou (4) Huizhuo Yuan (4) Yihe Deng (4) Sham M. Kakade (2) Yuanzhi Li (2) Jingfeng Wu (2) Dongruo Zhou (2)

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 $ΞΌ$ 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