![]() ![]() ![]() Mathematical and Scientific Machine Learning (MSML'2021), 2021. Yifei Huang, Yaodong Yu, Hongyang Zhang, Yi Ma, and Yuan Yao. Jordan.Īdversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients. On the Convergence of Stochastic Extragradient for Bilinear Games with Restarted Iteration Averaging.Ĭhris Junchi Li*, Yaodong Yu*, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. of the 25nd of the International Conference on Artificial Intelligence and Statistics (AISTATS'2022), 2022. Yaodong Yu*, Tianyi Lin*, Eric Mazumdar*, Michael I. įast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization. Journal of Machine Learning Research (JMLR'2022), 2022. Kwan Ho Ryan Chan*, Yaodong Yu*, Chong You*, Haozhi Qi, John Wright, Yi Ma. ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction. of the 39th International Conference on Machine Learning (ICML'2022), 2022. Tianyi Lin*, Aldo Pacchiano*, Yaodong Yu*, Michael I. Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback. Yaodong Yu*, Zitong Yang*, Alexander Wei, Yi Ma, Jacob Steinhardt. ![]() Predicting Out-of-Distribution Error with the Projection Norm. In Proceedings of the 2022 Empirical Methods in Natural Language Processing (EMNLP'2022 Findings), 2022. Jianfeng Chi, William Shand, Yaodong Yu, Kai-Wei Chang, Han Zhao and Yuan Tian. What You See is What You Get: Distributional Generalization for Algorithm Design in Deep Learning.īogdan Kulynych*, Yao-Yuan Yang*, Yaodong Yu, Jarosław Błasiok, Preetum Nakkiran.Ĭonditional Supervised Contrastive Learning for Fair Text Classification. of the 36th Conference on Advances in Neural Information Processing Systems (NeurIPS'2022), 2022. Yaodong Yu, Alexander Wei, Sai Praneeth Karimireddy, Yi Ma, Michael I. TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels. Yaodong Yu, Stephen Bates, Yi Ma, Michael I. Robust Calibration with Multi-domain Temperature Scaling. My goal is to make machine learning systems more robust. My research interests include topics in machine learning and optimization. from the Department of Computer Science, University of Virginia. from the Department of Mathematics at Nanjing University, and my M.S. I am a PhD student in the EECS department at UC Berkeley advised by Michael I. EECS Department, University of California, Berkeleyħth floor, Sutardja Dai Hall, Berkeley, CA 94720. ![]()
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