Chengchang Liu (刘程畅)

Chengchang Liu Ph.D candidate The Chinese University of Hong Kong Email: 7liuchengchang@gmail.com (recommended) ccliu22@cse.cuhk.edu.hk

About me

I am a Ph.D candidate at CUHK, under supervision of Prof. John C.S. Lui. I received a B.S. in Statistics from USTC at 2022.

Previously, I visited CUHK (SZ) in 2024, hosted by Prof. Zhi-Quan (Tom) Luo.

I am always open for possible collaborations or visiting opportunities from both academia and industry, please feel free to contact me.

Research (Google Scholar)

My research focuses on designing efficient methods for large-scale optimization problems. I work closely with Prof. Luo Luo.

My recent interest includes:

• The theory of second-order optimization;

• Distributed/Federated optimization;

• The intersection of optimization and quantum computing.

My research is supported by NSFC basic research scheme for PhD students (Second-Order Optimization for Large-Scale Machine Learning: Algorithms and Analysis).

Publications

1. An Enhanced Levenberg–Marquardt Method via Gram Reduction.
   Chengchang Liu, Luo Luo, John C.S. Lui.
   AAAI, 2025

2. Quantum Algorithms for Non-smooth Non-convex Optimization.
   Chengchang Liu, Chaowen Guan, Jianhao He, John C.S. Lui.
   NeurIPS, 2024

3. Communication Efficient Distributed Newton Method with Fast Convergence Rates.
   Chengchang Liu, Lesi Chen, Luo Luo, John C.S. Lui.
   KDD, 2023

4. Block Broyden's Methods for Solving Nonlinear Equations.
   Chengchang Liu, Cheng Chen, Luo Luo, John C.S. Lui.
   NeurIPS, 2023

5. Partial-Quasi-Newton Methods: Efficient Algorithms for Minimax Optimization Problems with Unbalanced Dimensionality.
   Chengchang Liu, Shuxian Bi, Luo Luo, John C.S. Lui.
   KDD, 2022 Best Paper Runner-Up

6. Quasi-Newton Methods for Saddle Point Problems.
   Chengchang Liu, Luo Luo.
   NeurIPS, 2022 Spotlight

7. Quantum Algorithm for Online Exp-concave Optimization.
   Jianhao He, Chengchang Liu, Xutong Liu, Lvzhou Li, John C.S. Lui.
   ICML, 2024

8. Communication Efficient Distributed Newton Method over Unreliable Networks.
   Ming Wen, Chengchang Liu, Yuedong Xu.
   AAAI, 2024

Preprints

1. Second-order Min-Max Optimization with Lazy Hessians.
   Lesi Chen, Chengchang Liu, Jingzhao Zhang.
   arXiv preprint, 2024

2. Symmetric Rank-k Method
   Chengchang Liu, Cheng Chen, Luo Luo.
   arXiv preprint, 2023

3. Regularized Newton Methods for Monotone Variational Inequalities with Hölder Continuous Jacobians.
   Chengchang Liu, Luo Luo.
   arXiv preprint, 2022

4. Incremental Gauss–Newton Methods with Superlinear Convergence Rates.
   Zhiling Zhou, Zhuanghua Liu, Chengchang Liu, Luo Luo.
   arXiv preprint, 2024

Services

• Conference Reviewer: NeurIPS 2023-24, ICLR 2024-25, AISTATS 2024, ICML 2024, AAAI 2025.