Publications and Preprints

Publications

• Stochastic Optimization for Machine Learning: Investigations on Bilevel Optimization and Large Learning Rates, PhD thesis.
  • Xuxing Chen
• Fully First-Order Methods for Decentralized Bilevel Optimization, IEEE TSP 2025 (to appear).
  • Xiaoyu Wang*, Xuxing Chen*, Shiqian Ma, Tong Zhang.
• Tuning-Free Decentralized Nonconvex Stochastic Optimization, Pacific Journal of Optimization 2025.
  • Jiaxiang Li, Xuxing Chen, Shiqian Ma, Mingyi Hong.
• Stochastic Approximation Algorithms for Nested Compositional Bi-level Optimization, Mathematical Programming 2025 (minor revision).
  • Xuxing Chen, Krishnakumar Balasubramanian, Saeed Ghadimi.
• Efficiently Escaping Saddle Points in Bilevel Optimization, JMLR 2025.
  • Minhui Huang*, Xuxing Chen*, Kaiyi Ji, Shiqian Ma, Lifeng Lai.
• Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data, NeurIPS 2024.
  • Xuxing Chen*, Abhishek Roy*, Yifan Hu, Krishnakumar Balasubramanian.
• Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions, JMLR 2024.
  • Xuxing Chen*, Tesi Xiao*, Krishnakumar Balasubramanian.
• From Stability to Chaos: Analyzing Gradient Descent Dynamics in Quadratic Regression, TMLR 2024.
  • Xuxing Chen, Krishnakumar Balasubramanian, Promit Ghosal, Bhavya Agrawalla.
• Decentralized Bilevel Optimization, Optimization Letters 2024.
  • Xuxing Chen, Minhui Huang, Shiqian Ma.
• Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity, ICML 2023.
  • Xuxing Chen, Minhui Huang, Shiqian Ma, Krishnakumar Balasubramanian.
• A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic Composite Optimization, UAI 2023.
  • Tesi Xiao*, Xuxing Chen*, Krishnakumar Balasubramanian, Saeed Ghadimi.

(‘*’ denotes equal contributions)