Bao, Yajie

10 publications

ICML 2025 Conformal Prediction with Cellwise Outliers: A Detect-Then-Impute Approach Qian Peng, Yajie Bao, Haojie Ren, Zhaojun Wang, Changliang Zou

NeurIPS 2025 Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention Shuang Wu, Youtian Lin, Feihu Zhang, Yifei Zeng, Yikang Yang, Yajie Bao, Jiachen Qian, Siyu Zhu, Xun Cao, Philip Torr, Yao Yao

ICLR 2025 Error-Quantified Conformal Inference for Time Series Junxi Wu, Dongjian Hu, Yajie Bao, Shu-Tao Xia, Changliang Zou

ICML 2024 Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective Yajie Bao, Michael Crawshaw, Mingrui Liu

ICLR 2023 EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data Michael Crawshaw, Yajie Bao, Mingrui Liu

NeurIPS 2023 Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds Michael Crawshaw, Yajie Bao, Mingrui Liu

NeurIPS 2023 Global Convergence Analysis of Local SGD for Two-Layer Neural Network Without Overparameterization Yajie Bao, Amarda Shehu, Mingrui Liu

UAI 2022 Byzantine-Tolerant Distributed Multiclass Sparse Linear Discriminant Analysis Yajie Bao, Weidong Liu, Xiaojun Mao, Weijia Xiong

ICML 2022 Fast Composite Optimization and Statistical Recovery in Federated Learning Yajie Bao, Michael Crawshaw, Shan Luo, Mingrui Liu

AISTATS 2021 One-Round Communication Efficient Distributed M-Estimation Yajie Bao, Weijia Xiong