| 2026 | AAAI | Decentralized Non-convex Stochastic Optimization with Heterogeneous Variance. | Hongxu Chen, Ke Wei, Luo Luo |
| 2026 | AAAI | Privacy Leaks by Adversaries: Adversarial Iterations for Membership Inference Attack. | Jing Xue, Zhishen Sun, Haishan Ye, Luo Luo, Xiangyu Chang, Guang Dai |
| 2026 | COLT | Faster Newton Methods for Convex and Nonconvex Optimization in Gradient Complexity. | Lesi Chen, Chengchang Liu, Luo Luo, Jingzhao Zhang |
| 2025 | AAAI | An Enhanced Levenberg-Marquardt Method via Gram Reduction. | Chengchang Liu, Luo Luo, John C. S. Lui |
| 2025 | COLT | Solving Convex-Concave Problems with 풪(ε | Lesi Chen, Chengchang Liu, Luo Luo, Jingzhao Zhang |
| 2025 | ICML | A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization. | Kunjie Ren, Luo Luo |
| 2024 | AAAI | Decentralized Gradient-Free Methods for Stochastic Non-smooth Non-convex Optimization. | Zhenwei Lin, Jingfan Xia, Qi Deng, Luo Luo |
| 2024 | AAAI | Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates. | Zhuanghua Liu, Luo Luo, Bryan Kian Hsiang Low |
| 2024 | AISTATS | An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization. | Lesi Chen, Haishan Ye, Luo Luo |
| 2024 | ICML | On the Complexity of Finite-Sum Smooth Optimization under the Polyak-Łojasiewicz Condition. | Yunyan Bai, Yuxing Liu, Luo Luo |
| 2024 | ICML | Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers. | Yuxing Liu, Lesi Chen, Luo Luo |
| 2024 | ICML | Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization. | Zhuanghua Liu, Cheng Chen, Luo Luo, Bryan Kian Hsiang Low |
| 2023 | ICML | Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization. | Lesi Chen, Jing Xu, Luo Luo |
| 2023 | KDD | Communication Efficient Distributed Newton Method with Fast Convergence Rates. | Chengchang Liu, Lesi Chen, Luo Luo, John C. S. Lui |
| 2022 | KDD | Partial-Quasi-Newton Methods: Efficient Algorithms for Minimax Optimization Problems with Unbalanced Dimensionality. | Chengchang Liu, Shuxian Bi, Luo Luo, John C. S. Lui |
| 2021 | AAAI | Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices. | Luo Luo, Cheng Chen, Guangzeng Xie, Haishan Ye |
| 2020 | ICML | Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems. | Guangzeng Xie, Luo Luo, Yijiang Lian, Zhihua Zhang |
| 2020 | IJCAI | Efficient and Robust High-Dimensional Linear Contextual Bandits. | Cheng Chen, Luo Luo, Weinan Zhang, Yong Yu, Yijiang Lian |
| 2018 | KDD | Sketched Follow-The-Regularized-Leader for Online Factorization Machine. | Luo Luo, Wenpeng Zhang, Zhihua Zhang, Wenwu Zhu, Tong Zhang, Jian Pei |
| 2017 | AAAI | Communication Lower Bounds for Distributed Convex Optimization: Partition Data on Features. | Zihao Chen, Luo Luo, Zhihua Zhang |
| 2017 | ICML | Approximate Newton Methods and Their Local Convergence. | Haishan Ye, Luo Luo, Zhihua Zhang |
| 2016 | IJCAI | Frequent Direction Algorithms for Approximate Matrix Multiplication with Applications in CCA. | Qiaomin Ye, Luo Luo, Zhihua Zhang |
| 2016 | UAI | Quasi-Newton Hamiltonian Monte Carlo. | Tianfan Fu, Luo Luo, Zhihua Zhang |
| 2015 | ICML | Support Matrix Machines. | Luo Luo, Yubo Xie, Zhihua Zhang, Wu-Jun Li |
| 2008 | SIGCSE | Will they stay or will they go? | Joanne McGrath Cohoon, Zhen Wu, Luo Luo |