Zirui Zhou

According to our database, Zirui Zhou authored at least 35 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Privacy-Preserving Deployment Mechanism for Service Function Chains Across Multiple Domains.

Jun Cai, Zirui Zhou, Zhongwei Huang, Wenlong Dai, Fei Richard Yu

IEEE Trans. Netw. Serv. Manag., February, 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, 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

CoRR, 2024

Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process.

Zhenan Fan, Bissan Ghaddar, Xinglu Wang, Linzi Xing, Yong Zhang, Zirui Zhou

CoRR, 2024

2023

Decentralized Composite Optimization in Stochastic Networks: A Dual Averaging Approach With Linear Convergence.

Changxin Liu, Zirui Zhou, Jian Pei, Yong Zhang, Yang Shi

IEEE Trans. Autom. Control., August, 2023

Iteration-Complexity of First-Order Augmented Lagrangian Methods for Convex Conic Programming.

Zhaosong Lu, Zirui Zhou

SIAM J. Optim., June, 2023

Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks.

Mehdi Seyfi, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Smart Initial Basis Selection for Linear Programs.

Zhenan Fan, Xinglu Wang, Oleksandr Yakovenko, Abdullah Ali Sivas, Owen Ren, Yong Zhang, Zirui Zhou

Proceedings of the International Conference on Machine Learning, 2023

2022

Non-convex exact community recovery in stochastic block model.

Peng Wang, Zirui Zhou, Anthony Man-Cho So

Math. Program., 2022

Penalty and Augmented Lagrangian Methods for Constrained DC Programming.

Zhaosong Lu, Zhe Sun, Zirui Zhou

Math. Oper. Res., 2022

Knowledge-Injected Federated Learning.

Zhenan Fan, Zirui Zhou, Jian Pei, Michael P. Friedlander, Jiajie Hu, Chengliang Li, Yong Zhang

CoRR, 2022

Revealing Unfair Models by Mining Interpretable Evidence.

Mohit Bajaj, Lingyang Chu, Vittorio Romaniello, Gursimran Singh, Jian Pei, Zirui Zhou, Lanjun Wang, Yong Zhang

CoRR, 2022

Fair and efficient contribution valuation for vertical federated learning.

Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Yong Zhang

CoRR, 2022

Improving Fairness for Data Valuation in Horizontal Federated Learning.

Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

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

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: EMNLP 2022 - Industry Track, Abu Dhabi, UAE, December 7, 2022

2021

Improving Fairness for Data Valuation in Federated Learning.

Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang

CoRR, 2021

Achieving Model Fairness in Vertical Federated Learning.

Changxin Liu, Zirui Zhou, Yang Shi, Jian Pei, Lingyang Chu, Yong Zhang

CoRR, 2021

FedFair: Training Fair Models In Cross-Silo Federated Learning.

Lingyang Chu, Lanjun Wang, Yanjie Dong, Jian Pei, Zirui Zhou, Yong Zhang

CoRR, 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

CoRR, 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

Proceedings of the NeurIPS 2022 Competition Track, 2021

Towards Fair Federated Learning.

Zirui Zhou, Lingyang Chu, Changxin Liu, Lanjun Wang, Jian Pei, Yong Zhang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Network-wide Traffic Signal Optimization under Connected Vehicles Environment.

Liang Hu, Lanjun Wang, Zirui Zhou, Zhenli Sheng, Yong Zhang

Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021

Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method.

Peng Wang, Huikang Liu, Zirui Zhou, Anthony Man-Cho So

Proceedings of the 38th International Conference on Machine Learning, 2021

Personalized Cross-Silo Federated Learning on Non-IID Data.

Yutao Huang, Lingyang Chu, Zirui Zhou, Lanjun Wang, Jiangchuan Liu, Jian Pei, Yong Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Personalized Federated Learning: An Attentive Collaboration Approach.

Yutao Huang, Lingyang Chu, Zirui Zhou, Lanjun Wang, Jiangchuan Liu, Jian Pei, Yong Zhang

CoRR, 2020

A Nearly-Linear Time Algorithm for Exact Community Recovery in Stochastic Block Model.

Peng Wang, Zirui Zhou, Anthony Man-Cho So

Proceedings of the 37th International Conference on Machine Learning, 2020

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

Nonmonotone Enhanced Proximal DC Algorithms for a Class of Structured Nonsmooth DC Programming.

Zhaosong Lu, Zirui Zhou

SIAM J. Optim., 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

Enhanced proximal DC algorithms with extrapolation for a class of structured nonsmooth DC minimization.

Zhaosong Lu, Zirui Zhou, Zhe Sun

Math. Program., 2019

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

A unified approach to error bounds for structured convex optimization problems.

Zirui Zhou, Anthony Man-Cho So

Math. Program., 2017

2015

\(\ell_{1, p}\)-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods.

Zirui Zhou, Qi Zhang, Anthony Man-Cho So

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Latent Aspect Mining via Exploring Sparsity and Intrinsic Information.

Yinqing Xu, Tianyi Lin, Wai Lam, Zirui Zhou, Hong Cheng, Anthony Man-Cho So

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

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

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

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

Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14-19, 2013, 2013