Zirui Zhou

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 38

Top Topics

Convex Minimization

Optimization Problems

Regularization Method

Top Venues

Publications

Linzi Xing, Xinglu Wang, Yuxi Feng, Zhenan Fan, Jing Xiong, Zhijiang Guo, Xiaojin Fu, Rindra Ramamonjison, Mahdi Mostajabdaveh, Xiongwei Han, Zirui Zhou, Yong Zhang
Towards Human-aligned Evaluation for Linear Programming Word Problems. LREC/COLING (2024)
Zirui Zhou, Junhao Liang, Zizhao Peng, Chao Fan, Fengwei An, Shiqi Yu
Gait Patterns as Biomarkers: A Video-Based Approach for Classifying Scoliosis. CoRR (2024)
Zhenan Fan, Bissan Ghaddar, Xinglu Wang, Linzi Xing, Yong Zhang, Zirui Zhou
Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process. CoRR (2024)
Xijun Li, Fangzhou Zhu, Hui-Ling Zhen, Weilin Luo, Meng Lu, Yimin Huang, Zhenan Fan, Zirui Zhou, Yufei Kuang, Zhihai Wang, Zijie Geng, Yang Li, Haoyang Liu, Zhiwu An, Muming Yang, Jianshu Li, Jie Wang, Junchi Yan, Defeng Sun, Tao Zhong, Yong Zhang, Jia Zeng, Mingxuan Yuan, Jianye Hao, Jun Yao, Kun Mao
Machine Learning Insides OptVerse AI Solver: Design Principles and Applications. CoRR (2024)
Jun Cai, Zirui Zhou, Zhongwei Huang, Wenlong Dai, Fei Richard Yu
Privacy-Preserving Deployment Mechanism for Service Function Chains Across Multiple Domains. IEEE Trans. Netw. Serv. Manag. 21 (1) (2024)
Zhenan Fan, Huang Fang, Xinglu Wang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Yong Zhang
Fair and Efficient Contribution Valuation for Vertical Federated Learning. ICLR (2024)
Changxin Liu, Zirui Zhou, Jian Pei, Yong Zhang, Yang Shi
Decentralized Composite Optimization in Stochastic Networks: A Dual Averaging Approach With Linear Convergence. IEEE Trans. Autom. Control. 68 (8) (2023)
Mehdi Seyfi, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks. ECML/PKDD (4) (2023)
Zhenan Fan, Xinglu Wang, Oleksandr Yakovenko, Abdullah Ali Sivas, Owen Ren, Yong Zhang, Zirui Zhou
Smart Initial Basis Selection for Linear Programs. ICML (2023)
Rindranirina Ramamonjison, Timothy T. Yu, Raymond Li, Haley Li, Giuseppe Carenini, Bissan Ghaddar, Shiqi He, Mahdi Mostajabdaveh, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang
NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions. CoRR (2023)
Zhaosong Lu, Zirui Zhou
Iteration-Complexity of First-Order Augmented Lagrangian Methods for Convex Conic Programming. SIAM J. Optim. 33 (2) (2023)
Mehdi Seyfi, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks. CoRR (2023)
Peng Wang, Zirui Zhou, Anthony Man-Cho So
Non-convex exact community recovery in stochastic block model. Math. Program. 195 (1) (2022)
Rindranirina Ramamonjison, Haley Li, Timothy T. Yu, Shiqi He, Vishnu Rengan, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang
Augmenting Operations Research with Auto-Formulation of Optimization Models from Problem Descriptions. CoRR (2022)
Mohit Bajaj, Lingyang Chu, Vittorio Romaniello, Gursimran Singh, Jian Pei, Zirui Zhou, Lanjun Wang, Yong Zhang
Revealing Unfair Models by Mining Interpretable Evidence. CoRR (2022)
Zhaosong Lu, Zhe Sun, Zirui Zhou
Penalty and Augmented Lagrangian Methods for Constrained DC Programming. Math. Oper. Res. 47 (3) (2022)
Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Yong Zhang
Fair and efficient contribution valuation for vertical federated learning. CoRR (2022)
Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang
Improving Fairness for Data Valuation in Horizontal Federated Learning. ICDE (2022)
Rindra Ramamonjison, Haley Li, Timothy T. Yu, Shiqi He, Vishnu Rengan, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang
Augmenting Operations Research with Auto-Formulation of Optimization Models From Problem Descriptions. EMNLP (Industry Track) (2022)
Zhenan Fan, Zirui Zhou, Jian Pei, Michael P. Friedlander, Jiajie Hu, Chengliang Li, Yong Zhang
Knowledge-Injected Federated Learning. CoRR (2022)
Peng Wang, Huikang Liu, Zirui Zhou, Anthony Man-Cho So
Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method. ICML (2021)
Rindranirina Ramamonjison, Timothy T. L. Yu, Raymond Li, Haley Li, Giuseppe Carenini, Bissan Ghaddar, Shiqi He, Mahdi Mostajabdaveh, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang
NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions. NeurIPS (Competition and Demos) (2021)
Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang
Improving Fairness for Data Valuation in Federated Learning. CoRR (2021)
Liang Hu, Lanjun Wang, Zirui Zhou, Zhenli Sheng, Yong Zhang
Network-wide Traffic Signal Optimization under Connected Vehicles Environment. ITSC (2021)
Liang Hu, Jiangcheng Zhu, Zirui Zhou, Ruiqing Cheng, Xiaolong Bai, Yong Zhang
An Optimal Resource Allocator of Elastic Training for Deep Learning Jobs on Cloud. CoRR (2021)
Changxin Liu, Zirui Zhou, Yang Shi, Jian Pei, Lingyang Chu, Yong Zhang
Achieving Model Fairness in Vertical Federated Learning. CoRR (2021)
Zirui Zhou, Lingyang Chu, Changxin Liu, Lanjun Wang, Jian Pei, Yong Zhang
Towards Fair Federated Learning. KDD (2021)
Yutao Huang, Lingyang Chu, Zirui Zhou, Lanjun Wang, Jiangchuan Liu, Jian Pei, Yong Zhang
Personalized Cross-Silo Federated Learning on Non-IID Data. AAAI (2021)
Lingyang Chu, Lanjun Wang, Yanjie Dong, Jian Pei, Zirui Zhou, Yong Zhang
FedFair: Training Fair Models In Cross-Silo Federated Learning. CoRR (2021)
Changxin Liu, Zirui Zhou, Jian Pei, Yong Zhang, Yang Shi
Decentralized Composite Optimization in Stochastic Networks: A Dual Averaging Approach with Linear Convergence. CoRR (2021)
Yutao Huang, Lingyang Chu, Zirui Zhou, Lanjun Wang, Jiangchuan Liu, Jian Pei, Yong Zhang
Personalized Federated Learning: An Attentive Collaboration Approach. CoRR (2020)
Peng Wang, Zirui Zhou, Anthony Man-Cho So
A Nearly-Linear Time Algorithm for Exact Community Recovery in Stochastic Block Model. ICML (2020)
Zhaosong Lu, Zirui Zhou
Nonmonotone Enhanced Proximal DC Algorithms for a Class of Structured Nonsmooth DC Programming. SIAM J. Optim. 29 (4) (2019)
Man-Chung Yue, Zirui Zhou, Anthony Man-Cho So
A family of inexact SQA methods for non-smooth convex minimization with provable convergence guarantees based on the Luo-Tseng error bound property. Math. Program. 174 (1-2) (2019)
Zhaosong Lu, Zirui Zhou, Zhe Sun
Enhanced proximal DC algorithms with extrapolation for a class of structured nonsmooth DC minimization. Math. Program. 176 (1-2) (2019)
Man-Chung Yue, Zirui Zhou, Anthony Man-Cho So
On the Quadratic Convergence of the Cubic Regularization Method under a Local Error Bound Condition. SIAM J. Optim. 29 (1) (2019)
Anthony Man-Cho So, Zirui Zhou
Non-asymptotic convergence analysis of inexact gradient methods for machine learning without strong convexity. Optim. Methods Softw. 32 (4) (2017)
Zirui Zhou, Anthony Man-Cho So
A unified approach to error bounds for structured convex optimization problems. Math. Program. 165 (2) (2017)
Zirui Zhou, Qi Zhang, Anthony Man-Cho So
\(\ell_{1, p}\)-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods. ICML (2015)
Zirui Zhou, Anthony Man-Cho So
A Unified Approach to Error Bounds for Structured Convex Optimization Problems. CoRR (2015)
Yinqing Xu, Tianyi Lin, Wai Lam, Zirui Zhou, Hong Cheng, Anthony Man-Cho So
Latent Aspect Mining via Exploring Sparsity and Intrinsic Information. CIKM (2014)
Ke Hou, Zirui Zhou, Anthony Man-Cho So, Zhi-Quan Luo
On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization. NIPS (2013)
Senshan Ji, Kam-Fung Sze, Zirui Zhou, Anthony Man-Cho So, Yinyu Ye
Beyond convex relaxation: A polynomial-time non-convex optimization approach to network localization. INFOCOM (2013)