Zhou, Ding-Xuan

21 publications

JMLR 2025 Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos Shao-Bo Lin, Xiaotong Liu, Di Wang, Hai Zhang, Ding-Xuan Zhou

JMLR 2024 Classification with Deep Neural Networks and Logistic Loss Zihan Zhang, Lei Shi, Ding-Xuan Zhou

JMLR 2024 Nonparametric Regression Using Over-Parameterized Shallow ReLU Neural Networks Yunfei Yang, Ding-Xuan Zhou

ICML 2023 Generalization Analysis for Contrastive Representation Learning Yunwen Lei, Tianbao Yang, Yiming Ying, Ding-Xuan Zhou

NeurIPS 2022 Stability and Generalization for Markov Chain Stochastic Gradient Methods Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou

JMLR 2021 On ADMM in Deep Learning: Convergence and Saturation-Avoidance Jinshan Zeng, Shao-Bo Lin, Yuan Yao, Ding-Xuan Zhou

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

JMLR 2020 Distributed Kernel Ridge Regression with Communications Shao-Bo Lin, Di Wang, Ding-Xuan Zhou

JMLR 2019 Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping Shao-Bo Lin, Yunwen Lei, Ding-Xuan Zhou

NeurIPS 2019 Optimal Stochastic and Online Learning with Individual Iterates Yunwen Lei, Peng Yang, Ke Tang, Ding-Xuan Zhou

JMLR 2017 Distributed Learning with Regularized Least Squares Shao-Bo Lin, Xin Guo, Ding-Xuan Zhou

JMLR 2017 Distributed Semi-Supervised Learning with Kernel Ridge Regression Xiangyu Chang, Shao-Bo Lin, Ding-Xuan Zhou

AISTATS 2016 Fast Convergence of Online Pairwise Learning Algorithms Martin Boissier, Siwei Lyu, Yiming Ying, Ding-Xuan Zhou

JMLR 2016 Iterative Regularization for Learning with Convex Loss Functions Junhong Lin, Lorenzo Rosasco, Ding-Xuan Zhou

JMLR 2016 Sparsity and Error Analysis of Empirical Feature-Based Regularization Schemes Xin Guo, Jun Fan, Ding-Xuan Zhou

JMLR 2015 Learning Theory of Randomized Kaczmarz Algorithm Junhong Lin, Ding-Xuan Zhou

JMLR 2009 Classification with Gaussians and Convex Loss Dao-Hong Xiang, Ding-Xuan Zhou

JMLR 2009 Online Learning with Samples Drawn from Non-Identical Distributions Ting Hu, Ding-Xuan Zhou

JMLR 2007 Learnability of Gaussians with Flexible Variances Yiming Ying, Ding-Xuan Zhou

JMLR 2006 Learning Coordinate Covariances via Gradients Sayan Mukherjee, Ding-Xuan Zhou

JMLR 2004 Support Vector Machine Soft Margin Classifiers: Error Analysis Di-Rong Chen, Qiang Wu, Yiming Ying, Ding-Xuan Zhou