Yuan Cao
73 papers · 2014–2026 · 15 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 14 separate collaboration groups - the largest holds only 40% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Yuan Cao?
5 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Quanquan Gu, Difan Zou, Zixiang Chen
29 papers
· 2019–2026
· NeurIPS, ICLR, ICML
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Towards Understanding Generalization in DP-GD: A Case Study in Training Two-Layer CNNs
AAAI 2026
On the Feature Learning in Diffusion Models
ICLR 2025
On the Power of Multitask Representation Learning with Gradient Descent
AISTATS 2025
Quantifying the Optimization and Generalization Advantages of Graph Neural Networks Over Multilayer Perceptrons
AISTATS 2025
Transformer Learns Optimal Variable Selection in Group-Sparse Classification
ICLR 2025
Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data
ICML 2024
Multiple Descent in the Multiple Random Feature Model
JMLR 2024
On the Comparison between Multi-modal and Single-modal Contrastive Learning
NeurIPS 2024
The Implicit Bias of Adam on Separable Data
NeurIPS 2024
Benign Overfitting in Adversarially Robust Linear Classification
UAI 2023
How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study
ICLR 2023
The Benefits of Mixup for Feature Learning
ICML 2023
The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks
COLT 2023
Understanding Train-Validation Split in Meta-Learning with Neural Networks
ICLR 2023
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization
ICLR 2023
Benign Overfitting in Two-layer Convolutional Neural Networks
NeurIPS 2022
Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
ICML 2021
How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?
ICLR 2021
Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise
ICML 2021
Risk Bounds for Over-parameterized Maximum Margin Classification on Sub-Gaussian Mixtures
NeurIPS 2021
Towards Understanding the Spectral Bias of Deep Learning
IJCAI 2021
A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks
NeurIPS 2020
Accelerated Factored Gradient Descent for Low-Rank Matrix Factorization
AISTATS 2020
Agnostic Learning of a Single Neuron with Gradient Descent
NeurIPS 2020
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks
IJCAI 2020
Generalization Error Bounds of Gradient Descent for Learning Over-Parameterized Deep ReLU Networks
AAAI 2020
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks
NeurIPS 2019
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks
NeurIPS 2019
Tight Sample Complexity of Learning One-hidden-layer Convolutional Neural Networks
NeurIPS 2019
9 papers whose co-authors appear nowhere else under this name
Geometry-driven OOD Detectors Are Class-Incremental Learners
CVPR 2026
Proxy Zero-Shot Hashing with Multimodal Fusion via Stable Diffusion
AAAI 2026
Vision-guided Text Mining for Unsupervised Cross-modal Hashing with Community Similarity Quantization
AAAI 2025
Attention boosted Individualized Regression
NeurIPS 2024
Can Public Large Language Models Help Private Cross-device Federated Learning?
NAACL 2024
Grammar Prompting for Domain-Specific Language Generation with Large Language Models
NeurIPS 2023
On the Channel Pruning using Graph Convolution Network for Convolutional Neural Network Acceleration
IJCAI 2022
Neural Decipherment via Minimum-Cost Flow: From Ugaritic to Linear B
ACL 2019
Online Learning in Tensor Space
ACL 2014