Sun, Defeng

12 publications

ICLR 2025 A Tight Convergence Analysis of Inexact Stochastic Proximal Point Algorithm for Stochastic Composite Optimization Problems Shulan Zhu, Chenglong Bao, Defeng Sun, Yancheng Yuan

JMLR 2025 Efficient Online Prediction for High-Dimensional Time Series via Joint Tensor Tucker Decomposition Zhenting Luan, Defeng Sun, Haoning Wang, Liping Zhang

JMLR 2025 Randomly Projected Convex Clustering Model: Motivation, Realization, and Cluster Recovery Guarantees Ziwen Wang, Yancheng Yuan, Jiaming Ma, Tieyong Zeng, Defeng Sun

JMLR 2024 Estimation of Sparse Gaussian Graphical Models with Hidden Clustering Structure Meixia Lin, Defeng Sun, Kim-Chuan Toh, Chengjing Wang

NeurIPS 2024 Globally Q-Linear Gauss-Newton Method for Overparameterized Non-Convex Matrix Sensing Xixi Jia, Fangchen Feng, Deyu Meng, Defeng Sun

AAAI 2023 Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework Shuai Wang, Yanqing Xu, Zhiguo Wang, Tsung-Hui Chang, Tony Q. S. Quek, Defeng Sun

JMLR 2023 MARS: A Second-Order Reduction Algorithm for High-Dimensional Sparse Precision Matrices Estimation Qian Li, Binyan Jiang, Defeng Sun

JMLR 2021 A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters Lei Yang, Jia Li, Defeng Sun, Kim-Chuan Toh

JMLR 2021 Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm Defeng Sun, Kim-Chuan Toh, Yancheng Yuan

JMLR 2020 A Sparse Semismooth Newton Based Proximal Majorization-Minimization Algorithm for Nonconvex Square-Root-Loss Regression Problems Peipei Tang, Chengjing Wang, Defeng Sun, Kim-Chuan Toh

JMLR 2019 Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method Ziyan Luo, Defeng Sun, Kim-Chuan Toh, Naihua Xiu

ICML 2018 An Efficient Semismooth Newton Based Algorithm for Convex Clustering Yancheng Yuan, Defeng Sun, Kim-Chuan Toh