Yu, Yaodong

40 publications

AISTATS 2025 Accuracy on the Wrong Line: On the Pitfalls of Noisy Data for Out-of-Distribution Generalisation Amartya Sanyal, Yaxi Hu, Yaodong Yu, Yian Ma, Yixin Wang, Bernhard Schölkopf

CVPR 2025 Adventurer: Optimizing Vision Mamba Architecture Designs for Efficiency Feng Wang, Timing Yang, Yaodong Yu, Sucheng Ren, Guoyizhe Wei, Angtian Wang, Wei Shao, Yuyin Zhou, Alan Yuille, Cihang Xie

ICML 2025 Attention-Only Transformers via Unrolled Subspace Denoising Peng Wang, Yifu Lu, Yaodong Yu, Druv Pai, Qing Qu, Yi Ma

ICML 2025 Scaling Laws in Patchification: An Image Is Worth 50,176 Tokens and More Feng Wang, Yaodong Yu, Wei Shao, Yuyin Zhou, Alan Yuille, Cihang Xie

ICLR 2025 Token Statistics Transformer: Linear-Time Attention via Variational Rate Reduction Ziyang Wu, Tianjiao Ding, Yifu Lu, Druv Pai, Jingyuan Zhang, Weida Wang, Yaodong Yu, Yi Ma, Benjamin David Haeffele

ICML 2024 A Global Geometric Analysis of Maximal Coding Rate Reduction Peng Wang, Huikang Liu, Druv Pai, Yaodong Yu, Zhihui Zhu, Qing Qu, Yi Ma

ICMLW 2024 Accuracy on the Wrong Line: On the Pitfalls of Noisy Data for OOD Generalisation Amartya Sanyal, Yaxi Hu, Yaodong Yu, Yian Ma, Yixin Wang, Bernhard Schölkopf

ICML 2024 Differentially Private Representation Learning via Image Captioning Tom Sander, Yaodong Yu, Maziar Sanjabi, Alain Oliviero Durmus, Yi Ma, Kamalika Chaudhuri, Chuan Guo

CPAL 2024 Emergence of Segmentation with Minimalistic White-Box Transformers Yaodong Yu, Tianzhe Chu, Shengbang Tong, Ziyang Wu, Druv Pai, Sam Buchanan, Yi Ma

ICLR 2024 Masked Completion via Structured Diffusion with White-Box Transformers Druv Pai, Sam Buchanan, Ziyang Wu, Yaodong Yu, Yi Ma

NeurIPS 2024 Scaling White-Box Transformers for Vision Jinrui Yang, Xianhang Li, Druv Pai, Yuyin Zhou, Yi Ma, Yaodong Yu, Cihang Xie

ICML 2024 ViP: A Differentially Private Foundation Model for Computer Vision Yaodong Yu, Maziar Sanjabi, Yi Ma, Kamalika Chaudhuri, Chuan Guo

JMLR 2024 White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is? Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Hao Bai, Yuexiang Zhai, Benjamin D. Haeffele, Yi Ma

NeurIPSW 2023 A Study on the Calibration of In-Context Learning Hanlin Zhang, YiFan Zhang, Yaodong Yu, Dhruv Madeka, Dean Foster, Eric P. Xing, Himabindu Lakkaraju, Sham M. Kakade

NeurIPSW 2023 Emergence of Segmentation with Minimalistic White-Box Transformers Yaodong Yu, Tianzhe Chu, Shengbang Tong, Ziyang Wu, Druv Pai, Sam Buchanan, Yi Ma

ICML 2023 Federated Conformal Predictors for Distributed Uncertainty Quantification Charles Lu, Yaodong Yu, Sai Praneeth Karimireddy, Michael Jordan, Ramesh Raskar

ICMLW 2023 Federated Conformal Predictors for Distributed Uncertainty Quantification Charles Lu, Yaodong Yu, Sai Praneeth Karimireddy, Michael Jordan, Ramesh Raskar

ICMLW 2023 SCAFF-PD: Communication Efficient Fair and Robust Federated Learning Yaodong Yu, Sai Praneeth Karimireddy, Yi Ma, Michael Jordan

NeurIPS 2023 White-Box Transformers via Sparse Rate Reduction Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin Haeffele, Yi Ma

AISTATS 2022 Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization Yaodong Yu, Tianyi Lin, Eric V. Mazumdar, Michael Jordan

AISTATS 2022 On the Convergence of Stochastic Extragradient for Bilinear Games Using Restarted Iteration Averaging Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael Jordan

ICML 2022 Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback Tianyi Lin, Aldo Pacchiano, Yaodong Yu, Michael Jordan

ICML 2022 Predicting Out-of-Distribution Error with the Projection Norm Yaodong Yu, Zitong Yang, Alexander Wei, Yi Ma, Jacob Steinhardt

JMLR 2022 ReduNet: A White-Box Deep Network from the Principle of Maximizing Rate Reduction Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma

NeurIPS 2022 Robust Calibration with Multi-Domain Temperature Scaling Yaodong Yu, Stephen Bates, Yi Ma, Michael I. Jordan

ICMLW 2022 Robust Calibration with Multi-Domain Temperature Scaling Yaodong Yu, Stephen Bates, Yi Ma, Michael Jordan

NeurIPS 2022 TCT: Convexifying Federated Learning Using Bootstrapped Neural Tangent Kernels Yaodong Yu, Alexander Wei, Sai Praneeth Karimireddy, Yi Ma, Michael I. Jordan

NeurIPS 2022 What You See Is What You Get: Principled Deep Learning via Distributional Generalization Bogdan Kulynych, Yao-Yuan Yang, Yaodong Yu, Jarosław Błasiok, Preetum Nakkiran

NeurIPSW 2022 What You See Is What You Get: Principled Deep Learning via Distributional Generalization Bogdan Kulynych, Yao-Yuan Yang, Yaodong Yu, Jaroslaw Blasiok, Preetum Nakkiran

NeurIPSW 2021 An Empirical Study of Pre-Trained Vision Models on Out-of-Distribution Generalization Yaodong Yu, Heinrich Jiang, Dara Bahri, Hossein Mobahi, Seungyeon Kim, Ankit Singh Rawat, Andreas Veit, Yi Ma

NeurIPSW 2021 The Effect of Model Size on Worst-Group Generalization Alan Le Pham, Eunice Chan, Vikranth Srivatsa, Dhruba Ghosh, Yaoqing Yang, Yaodong Yu, Ruiqi Zhong, Joseph E. Gonzalez, Jacob Steinhardt

NeurIPS 2020 Boundary Thickness and Robustness in Learning Models Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E Gonzalez, Kannan Ramchandran, Michael W. Mahoney

NeurIPS 2020 Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction Yaodong Yu, Kwan Ho Ryan Chan, Chong You, Chaobing Song, Yi Ma

ICML 2020 Rethinking Bias-Variance Trade-Off for Generalization of Neural Networks Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma

AISTATS 2019 Learning One-Hidden-Layer ReLU Networks via Gradient Descent Xiao Zhang, Yaodong Yu, Lingxiao Wang, Quanquan Gu

ICML 2019 Theoretically Principled Trade-Off Between Robustness and Accuracy Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric Xing, Laurent El Ghaoui, Michael Jordan

ICML 2018 A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery Xiao Zhang, Lingxiao Wang, Yaodong Yu, Quanquan Gu

AAAI 2018 Data Poisoning Attacks on Multi-Task Relationship Learning Mengchen Zhao, Bo An, Yaodong Yu, Sulin Liu, Sinno Jialin Pan

NeurIPS 2018 Third-Order Smoothness Helps: Faster Stochastic Optimization Algorithms for Finding Local Minima Yaodong Yu, Pan Xu, Quanquan Gu

UAI 2017 Communication-Efficient Distributed Primal-Dual Algorithm for Saddle Point Problem Yaodong Yu, Sulin Liu, Sinno Jialin Pan