Cao, Yuan

64 publications

AAAI 2025 Deep Graph Online Hashing for Multi-Label Image Retrieval Yuan Cao, Xiangru Chen, Zifan Liu, Wenzhe Jia, Fanlei Meng, Jie Gui

ICLR 2025 On the Feature Learning in Diffusion Models Andi Han, Wei Huang, Yuan Cao, Difan Zou

AISTATS 2025 On the Power of Multitask Representation Learning with Gradient Descent Qiaobo Li, Zixiang Chen, Yihe Deng, Yiwen Kou, Yuan Cao, Quanquan Gu

NeurIPS 2025 On the Robustness of Transformers Against Context Hijacking for Linear Classification Tianle Li, Chenyang Zhang, Xingwu Chen, Yuan Cao, Difan Zou

MLJ 2025 Per-Example Gradient Regularization Improves Learning Signals from Noisy Data Xuran Meng, Yuan Cao, Difan Zou

AISTATS 2025 Quantifying the Optimization and Generalization Advantages of Graph Neural Networks over Multilayer Perceptrons Wei Huang, Yuan Cao, Haonan Wang, Xin Cao, Taiji Suzuki

NeurIPS 2025 Towards Understanding Transformers in Learning Random Walks Wei Shi, Yuan Cao

ICLR 2025 Transformer Learns Optimal Variable Selection in Group-Sparse Classification Chenyang Zhang, Xuran Meng, Yuan Cao

NeurIPS 2025 Understanding the Generalization of Stochastic Gradient Adam in Learning Neural Networks Xuan Tang, Han Zhang, Yuan Cao, Difan Zou

AAAI 2025 Vision-Guided Text Mining for Unsupervised Cross-Modal Hashing with Community Similarity Quantization Haozhi Fan, Yuan Cao

NeurIPS 2024 Attention Boosted Individualized Regression Guang Yang, Yuan Cao, Long Feng

ICML 2024 Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data Xuran Meng, Difan Zou, Yuan Cao

NeurIPS 2024 Global Convergence in Training Large-Scale Transformers Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason M. Klusowski, Jianqing Fan

ICMLW 2024 Gradient Descent Robustly Learns the Intrinsic Dimension of Data in Training Convolutional Neural Networks Chenyang Zhang, Gao Peifeng, Difan Zou, Yuan Cao

ECCV 2024 IG Captioner: Information Gain Captioners Are Strong Zero-Shot Classifiers Chenglin Yang, Siyuan Qiao, Yuan Cao, Yu Zhang, Tao Zhu, Alan Yuille, Jiahui Yu

JMLR 2024 Multiple Descent in the Multiple Random Feature Model Xuran Meng, Jianfeng Yao, Yuan Cao

NeurIPS 2024 On the Comparison Between Multi-Modal and Single-Modal Contrastive Learning Wei Huang, Andi Han, Yongqiang Chen, Yuan Cao, Zhiqiang Xu, Taiji Suzuki

TMLR 2024 On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization Dongruo Zhou, Jinghui Chen, Yuan Cao, Ziyan Yang, Quanquan Gu

NeurIPS 2024 One-Layer Transformer Provably Learns One-Nearest Neighbor in Context Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang

AAAI 2024 Taxonomy Driven Fast Adversarial Training Kun Tong, Chengze Jiang, Jie Gui, Yuan Cao

NeurIPS 2024 The Implicit Bias of Adam on Separable Data Chenyang Zhang, Difan Zou, Yuan Cao

ICMLW 2024 The Implicit Bias of Adam on Separable Data Chenyang Zhang, Difan Zou, Yuan Cao

UAI 2023 Benign Overfitting in Adversarially Robust Linear Classification Jinghui Chen, Yuan Cao, Quanquan Gu

NeurIPS 2023 Binarized Neural Machine Translation Yichi Zhang, Ankush Garg, Yuan Cao, Lukasz Lew, Behrooz Ghorbani, Zhiru Zhang, Orhan Firat

ICMLW 2023 Can Public Large Language Models Help Private Cross-Device Federated Learning? Boxin Wang, Yibo Jacky Zhang, Yuan Cao, Bo Li, Hugh Brendan McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer

ICMLW 2023 Can Public Large Language Models Help Private Cross-Device Federated Learning? Boxin Wang, Yibo Jacky Zhang, Yuan Cao, Bo Li, Hugh Brendan McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer

AAAI 2023 Fast Online Hashing with Multi-Label Projection Wenzhe Jia, Yuan Cao, Junwei Liu, Jie Gui

NeurIPS 2023 Grammar Prompting for Domain-Specific Language Generation with Large Language Models Bailin Wang, Zi Wang, Xuezhi Wang, Yuan Cao, Rif A. Saurous, Yoon Kim

NeurIPSW 2023 Graph Neural Networks Benefit from Structural Information Provably: A Feature Learning Perspective Wei Huang, Yuan Cao, Haonan Wang, Xin Cao, Taiji Suzuki

AAAI 2023 Graph Structure Learning on User Mobility Data for Social Relationship Inference Guangming Qin, Lexue Song, Yanwei Yu, Chao Huang, Wenzhe Jia, Yuan Cao, Junyu Dong

ICLR 2023 How Does Semi-Supervised Learning with Pseudo-Labelers Work? a Case Study Yiwen Kou, Zixiang Chen, Yuan Cao, Quanquan Gu

ICLR 2023 ReAct: Synergizing Reasoning and Acting in Language Models Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R Narasimhan, Yuan Cao

NeurIPSW 2023 RoboVQA: Multimodal Long-Horizon Reasoningfor Robotics Pierre Sermanet, Tianli Ding, Jeffrey Zhao, Fei Xia, Debidatta Dwibedi, Keerthana Gopalakrishnan, Christine Chan, Gabriel Dulac-Arnold, Sharath Maddineni, Nikhil Joshi, Pete Florence, Wei Han, Robert Baruch, Yao Lu, Suvir Mirchandani, Peng Xu, Pannag Sanketi, Karol Hausman, Izhak Shafran, Brian Ichter, Yuan Cao

ICML 2023 The Benefits of Mixup for Feature Learning Difan Zou, Yuan Cao, Yuanzhi Li, Quanquan Gu

COLT 2023 The Implicit Bias of Batch Normalization in Linear Models and Two-Layer Linear Convolutional Neural Networks Yuan Cao, Difan Zou, Yuanzhi Li, Quanquan Gu

NeurIPS 2023 Tree of Thoughts: Deliberate Problem Solving with Large Language Models Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, Karthik Narasimhan

ICLR 2023 Understanding Train-Validation Split in Meta-Learning with Neural Networks Xinzhe Zuo, Zixiang Chen, Huaxiu Yao, Yuan Cao, Quanquan Gu

ICLR 2023 Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization Difan Zou, Yuan Cao, Yuanzhi Li, Quanquan Gu

NeurIPS 2022 Benign Overfitting in Two-Layer Convolutional Neural Networks Yuan Cao, Zixiang Chen, Misha Belkin, Quanquan Gu

IJCAI 2022 On the Channel Pruning Using Graph Convolution Network for Convolutional Neural Network Acceleration Di Jiang, Yuan Cao, Qiang Yang

NeurIPSW 2022 ReAct: Synergizing Reasoning and Acting in Language Models Shunyu Yao, Jeffrey Zhao, Dian Yu, Izhak Shafran, Karthik R Narasimhan, Yuan Cao

AAAI 2022 SGD-X: A Benchmark for Robust Generalization in Schema-Guided Dialogue Systems Harrison Lee, Raghav Gupta, Abhinav Rastogi, Yuan Cao, Bin Zhang, Yonghui Wu

ICLR 2022 SimVLM: Simple Visual Language Model Pretraining with Weak Supervision Zirui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, Yuan Cao

IJCAI 2021 A Comprehensive Survey on Image Dehazing Based on Deep Learning Jie Gui, Xiaofeng Cong, Yuan Cao, Wenqi Ren, Jun Zhang, Jing Zhang, Dacheng Tao

ICML 2021 Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins Spencer Frei, Yuan Cao, Quanquan Gu

ICLR 2021 Gradient Vaccine: Investigating and Improving Multi-Task Optimization in Massively Multilingual Models Zirui Wang, Yulia Tsvetkov, Orhan Firat, Yuan Cao

ICLR 2021 How Much Over-Parameterization Is Sufficient to Learn Deep ReLU Networks? Zixiang Chen, Yuan Cao, Difan Zou, Quanquan Gu

ICML 2021 Provable Generalization of SGD-Trained Neural Networks of Any Width in the Presence of Adversarial Label Noise Spencer Frei, Yuan Cao, Quanquan Gu

NeurIPS 2021 Risk Bounds for Over-Parameterized Maximum Margin Classification on Sub-Gaussian Mixtures Yuan Cao, Quanquan Gu, Mikhail Belkin

ICLR 2021 The Geometry of Integration in Text Classification RNNs Kyle Aitken, Vinay Venkatesh Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan

IJCAI 2021 Towards Understanding the Spectral Bias of Deep Learning Yuan Cao, Zhiying Fang, Yue Wu, Ding-Xuan Zhou, Quanquan Gu

NeurIPS 2021 Understanding How Encoder-Decoder Architectures Attend Kyle Aitken, Vinay Ramasesh, Yuan Cao, Niru Maheswaranathan

NeurIPS 2020 A Generalized Neural Tangent Kernel Analysis for Two-Layer Neural Networks Zixiang Chen, Yuan Cao, Quanquan Gu, Tong Zhang

AISTATS 2020 Accelerated Factored Gradient Descent for Low-Rank Matrix Factorization Dongruo Zhou, Yuan Cao, Quanquan Gu

NeurIPS 2020 Agnostic Learning of a Single Neuron with Gradient Descent Spencer Frei, Yuan Cao, Quanquan Gu

IJCAI 2020 Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks Jinghui Chen, Dongruo Zhou, Yiqi Tang, Ziyan Yang, Yuan Cao, Quanquan Gu

AAAI 2020 Generalization Error Bounds of Gradient Descent for Learning Over-Parameterized Deep ReLU Networks Yuan Cao, Quanquan Gu

MLJ 2020 Gradient Descent Optimizes Over-Parameterized Deep ReLU Networks Difan Zou, Yuan Cao, Dongruo Zhou, Quanquan Gu

NeurIPS 2020 Your GAN Is Secretly an Energy-Based Model and You Should Use Discriminator Driven Latent Sampling Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio

NeurIPS 2019 Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks Spencer Frei, Yuan Cao, Quanquan Gu

NeurIPS 2019 Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks Yuan Cao, Quanquan Gu

ICLR 2019 Hierarchical Generative Modeling for Controllable Speech Synthesis Wei-Ning Hsu, Yu Zhang, Ron J. Weiss, Heiga Zen, Yonghui Wu, Yuxuan Wang, Yuan Cao, Ye Jia, Zhifeng Chen, Jonathan Shen, Patrick Nguyen, Ruoming Pang

NeurIPS 2019 Tight Sample Complexity of Learning One-Hidden-Layer Convolutional Neural Networks Yuan Cao, Quanquan Gu

ICML 2018 The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference Hao Lu, Yuan Cao, Zhuoran Yang, Junwei Lu, Han Liu, Zhaoran Wang