Beyond convex relaxation: A polynomial-time non-convex optimization approach to network localization. - Senshan Ji; Kam-Fung Sze; Zirui Zhou; Anthony Man-Cho So; Yinyu Ye 001 (INFOCOM, 2013)

On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization. - Ke Hou; Zirui Zhou; Anthony Man-Cho So; Zhi-Quan Luo (NIPS, 2013)

Latent Aspect Mining via Exploring Sparsity and Intrinsic Information. - Yinqing Xu; Tianyi Lin; Wai Lam; Zirui Zhou; Hong Cheng 001; Anthony Man-Cho So (CIKM, 2014)

( ell_{1, p} )-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods. - Zirui Zhou; Qi Zhang; Anthony Man-Cho So (ICML, 2015)

A unified approach to error bounds for structured convex optimization problems. - Zirui Zhou; Anthony Man-Cho So (Math. Program., 2017)

Non-asymptotic convergence analysis of inexact gradient methods for machine learning without strong convexity. - Anthony Man-Cho So; Zirui Zhou (Optim. Methods Softw., 2017)

Enhanced proximal DC algorithms with extrapolation for a class of structured nonsmooth DC minimization. - Zhaosong Lu; Zirui Zhou; Zhe Sun (Math. Program., 2019)

A family of inexact SQA methods for non-smooth convex minimization with provable convergence guarantees based on the Luo-Tseng error bound property. - Man-Chung Yue; Zirui Zhou; Anthony Man-Cho So (Math. Program., 2019)

Nonmonotone Enhanced Proximal DC Algorithms for a Class of Structured Nonsmooth DC Programming. - Zhaosong Lu; Zirui Zhou (SIAM J. Optim., 2019)

On the Quadratic Convergence of the Cubic Regularization Method under a Local Error Bound Condition. - Man-Chung Yue; Zirui Zhou; Anthony Man-Cho So (SIAM J. Optim., 2019)

A Nearly-Linear Time Algorithm for Exact Community Recovery in Stochastic Block Model. - Peng Wang 098; Zirui Zhou; Anthony Man-Cho So (ICML, 2020)

Personalized Federated Learning: An Attentive Collaboration Approach. - Yutao Huang; Lingyang Chu; Zirui Zhou; Lanjun Wang; Jiangchuan Liu; Jian Pei 001; Yong Zhang 004 (CoRR, 2020)

Personalized Cross-Silo Federated Learning on Non-IID Data. - Yutao Huang; Lingyang Chu; Zirui Zhou; Lanjun Wang; Jiangchuan Liu; Jian Pei 001; Yong Zhang 004 (AAAI, 2021)

Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method. - Peng Wang 098; Huikang Liu; Zirui Zhou; Anthony Man-Cho So (ICML, 2021)

Network-wide Traffic Signal Optimization under Connected Vehicles Environment. - Liang Hu; Lanjun Wang; Zirui Zhou; Zhenli Sheng; Yong Zhang 004 (ITSC, 2021)

Towards Fair Federated Learning. - Zirui Zhou; Lingyang Chu; Changxin Liu 001; Lanjun Wang; Jian Pei 001; Yong Zhang 004 (KDD, 2021)

NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions. - 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 004 (NeurIPS (Competition and Demos), 2021)

An Optimal Resource Allocator of Elastic Training for Deep Learning Jobs on Cloud. - Liang Hu; Jiangcheng Zhu; Zirui Zhou; Ruiqing Cheng; Xiaolong Bai; Yong Zhang 004 (CoRR, 2021)

FedFair: Training Fair Models In Cross-Silo Federated Learning. - Lingyang Chu; Lanjun Wang; Yanjie Dong; Jian Pei 001; Zirui Zhou; Yong Zhang 004 (CoRR, 2021)

Achieving Model Fairness in Vertical Federated Learning. - Changxin Liu 001; Zirui Zhou; Yang Shi 001; Jian Pei 001; Lingyang Chu; Yong Zhang 004 (CoRR, 2021)

Improving Fairness for Data Valuation in Federated Learning. - Zhenan Fan; Huang Fang; Zirui Zhou; Jian Pei 001; Michael P. Friedlander; Changxin Liu 001; Yong Zhang 004 (CoRR, 2021)

Augmenting Operations Research with Auto-Formulation of Optimization Models From Problem Descriptions. - Rindra Ramamonjison; Haley Li; Timothy T. L. Yu; Shiqi He; Vishnu Rengan; Amin Banitalebi-Dehkordi; Zirui Zhou; Yong Zhang 004 (EMNLP (Industry Track), 2022)

Improving Fairness for Data Valuation in Horizontal Federated Learning. - Zhenan Fan; Huang Fang; Zirui Zhou; Jian Pei 001; Michael P. Friedlander; Changxin Liu 001; Yong Zhang 004 (ICDE, 2022)

Fair and efficient contribution valuation for vertical federated learning. - Zhenan Fan; Huang Fang; Zirui Zhou; Jian Pei 001; Michael P. Friedlander; Yong Zhang 004 (CoRR, 2022)

Revealing Unfair Models by Mining Interpretable Evidence. - Mohit Bajaj; Lingyang Chu; Vittorio Romaniello; Gursimran Singh; Jian Pei 001; Zirui Zhou; Lanjun Wang; Yong Zhang 004 (CoRR, 2022)

Knowledge-Injected Federated Learning. - Zhenan Fan; Zirui Zhou; Jian Pei 001; Michael P. Friedlander; Jiajie Hu; Chengliang Li; Yong Zhang 004 (CoRR, 2022)

Penalty and Augmented Lagrangian Methods for Constrained DC Programming. - Zhaosong Lu; Zhe Sun; Zirui Zhou (Math. Oper. Res., 2022)

Non-convex exact community recovery in stochastic block model. - Peng Wang 098; Zirui Zhou; Anthony Man-Cho So (Math. Program., 2022)

Smart Initial Basis Selection for Linear Programs. - Zhenan Fan; Xinglu Wang; Oleksandr Yakovenko; Abdullah Ali Sivas; Owen Ren; Yong Zhang 004; Zirui Zhou (ICML, 2023)

Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks. - Mehdi Seyfi; Amin Banitalebi-Dehkordi; Zirui Zhou; Yong Zhang 004 (ECML/PKDD (4), 2023)

Iteration-Complexity of First-Order Augmented Lagrangian Methods for Convex Conic Programming. - Zhaosong Lu; Zirui Zhou (SIAM J. Optim., 2023)

Decentralized Composite Optimization in Stochastic Networks: A Dual Averaging Approach With Linear Convergence. - Changxin Liu 001; Zirui Zhou; Jian Pei 001; Yong Zhang 004; Yang Shi 001 (IEEE Trans. Autom. Control., 2023)

Training Fair Models in Federated Learning without Data Privacy Infringement. - Xin Che; Jingdi Hu; Zirui Zhou; Yong Zhang; Lingyang Chu (IEEE Big Data, 2024)

Towards Human-aligned Evaluation for Linear Programming Word Problems. - Linzi Xing; Xinglu Wang; Yuxi Feng; Zhenan Fan; Jing Xiong; Zhijiang Guo; Xiaojin Fu; Rindra Ramamonjison; Mahdi Mostajabdaveh; Xiongwei Han; Zirui Zhou; Yong Zhang 004 (LREC/COLING, 2024)

Fair and Efficient Contribution Valuation for Vertical Federated Learning. - Zhenan Fan; Huang Fang; Xinglu Wang; Zirui Zhou; Jian Pei 001; Michael P. Friedlander; Yong Zhang 004 (ICLR, 2024)

Gait Patterns as Biomarkers: A Video-Based Approach for Classifying Scoliosis. - Zirui Zhou; Junhao Liang; Zizhao Peng; Chao Fan 001; Fengwei An; Shiqi Yu 001 (MICCAI (5), 2024)

Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process. - Zhenan Fan; Bissan Ghaddar; Xinglu Wang; Linzi Xing; Yong Zhang 004; Zirui Zhou (CoRR, 2024)

Machine Learning Insides OptVerse AI Solver: Design Principles and Applications. - 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 197; et al. (CoRR, 2024)

Evaluating LLM Reasoning in the Operations Research Domain with ORQA. - Mahdi Mostajabdaveh; Timothy T. Yu; Samarendra Chandan Bindu Dash; Rindranirina Ramamonjison; Jabo Serge Byusa; Giuseppe Carenini; Zirui Zhou; Yong Zhang 004 (CoRR, 2024)

Privacy-Preserving Deployment Mechanism for Service Function Chains Across Multiple Domains. - Jun Cai 002; Zirui Zhou; Zhongwei Huang; Wenlong Dai; Fei Richard Yu (IEEE Trans. Netw. Serv. Manag., 2024)

Optimization modeling and verification from problem specifications using a multi-agent multi-stage LLM framework. - Mahdi Mostajabdaveh; Timothy T. L. Yu; Rindranirina Ramamonjison; Giuseppe Carenini; Zirui Zhou; Yong Zhang 004 (INFOR Inf. Syst. Oper. Res., 2024)

GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models Through Statistically-Guided Geo-Prototyping. - Bang An 002; Xun Zhou 001; Zirui Zhou; Ronilo J. Ragodos; Zenglin Xu; Jun Luo 007 (AAAI, 2025)

Learn2Aggregate: Supervised Generation of Chvatal-Gomory Cuts Using Graph Neural Networks. - Arnaud Deza; Elias B. Khalil; Zhenan Fan; Zirui Zhou; Yong Zhang 004 (AAAI, 2025)

Evaluating LLM Reasoning in the Operations Research Domain with ORQA. - Mahdi Mostajabdaveh; Timothy Tin Long Yu; Samarendra Chandan Bindu Dash; Rindra Ramamonjison; Jabo Serge Byusa; Giuseppe Carenini; Zirui Zhou; Yong Zhang 004 (AAAI, 2025)

Decompositional Neural Scene Reconstruction with Generative Diffusion Prior. - Junfeng Ni; Yu Liu; Ruijie Lu; Zirui Zhou; Song-Chun Zhu; Yixin Chen 003; Siyuan Huang 001 (CVPR, 2025)

SMARTAPS: Tool-augmented LLMs for Operations Management. - Timothy Tin Long Yu; Mahdi Mostajabdaveh; Jabo Serge Byusa; Rindra Ramamonjison; Giuseppe Carenini; Kun Mao 001; Zirui Zhou; Yong Zhang 004 (CoRR, 2025)

EvoCut: Strengthening Integer Programs via Evolution-Guided Language Models. - Milad Yazdani; Mahdi Mostajabdaveh; Samin Aref; Zirui Zhou (CoRR, 2025)

Discrete Optimization of Min-Max Violation and its Applications Across Computational Sciences. - Cheikh Ahmed; Mahdi Mostajabdaveh; Samin Aref; Zirui Zhou (CoRR, 2025)