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Jiawei Zhang 0007
Person information
- affiliation: Chinese University of Hong Kong, School of Science and Engineering, Shenzhen, China
- affiliation: Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, Cambridge, MA, USA
Other persons with the same name
- Jiawei Zhang (aka: Jia-Wei Zhang, Jia Wei Zhang) — disambiguation page
- Jiawei Zhang 0001
— University of California, Davis, Department of Computer Science, IFM Lab, CA, USA (and 2 more)
- Jiawei Zhang 0002
— SenseTime Research, Shenzhen, China (and 1 more)
- Jiawei Zhang 0003 — Purdue University, West Lafayette, IN, USA
- Jiawei Zhang 0004
— Beijing University of Posts and Telecommunication, State Key Laboratory of Information Photonics and Optical Communications, China
- Jiawei Zhang 0006
— New York University, Department of Information, Operations and Management Sciences, Stern School of Business, NY, USA (and 1 more)
- Jiawei Zhang 0008 — East China Jiaotong University, China
- Jia-Wei Zhang 0009 (aka: Jiawei Zhang 0009) — Guangxi University, School of Business Administration, Nanning, China
- Jia-Wei Zhang 0010 (aka: Jiawei Zhang 0010) — Northeast Forestry University, Electromechanical Engineering Academy, Harbin, China
- Jiawei Zhang 0011
— Xidian University, School of Cyber Engineering, Xi'an, China
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Journal Articles
- 2022
- [j4]Jiawei Zhang
, Zhi-Quan Luo:
A Global Dual Error Bound and Its Application to the Analysis of Linearly Constrained Nonconvex Optimization. SIAM J. Optim. 32(3): 2319-2346 (2022) - [j3]Jiawei Zhang, Songyang Ge
, Tsung-Hui Chang
, Zhi-Quan Luo
:
Decentralized Non-Convex Learning With Linearly Coupled Constraints: Algorithm Designs and Application to Vertical Learning Problem. IEEE Trans. Signal Process. 70: 3312-3327 (2022) - 2021
- [j2]Zhiguo Wang
, Jiawei Zhang, Tsung-Hui Chang
, Jian Li
, Zhi-Quan Luo:
Distributed Stochastic Consensus Optimization With Momentum for Nonconvex Nonsmooth Problems. IEEE Trans. Signal Process. 69: 4486-4501 (2021) - 2020
- [j1]Jiawei Zhang, Zhi-Quan Luo:
A Proximal Alternating Direction Method of Multiplier for Linearly Constrained Nonconvex Minimization. SIAM J. Optim. 30(3): 2272-2302 (2020)
Conference and Workshop Papers
- 2023
- [c8]Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang:
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation. ICML 2023: 26769-26791 - 2022
- [c7]Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang:
What is a Good Metric to Study Generalization of Minimax Learners? NeurIPS 2022 - 2021
- [c6]Congliang Chen, Jiawei Zhang, Li Shen, Peilin Zhao, Zhi-Quan Luo:
Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization. AISTATS 2021: 1594-1602 - [c5]Jiawei Zhang, Yushun Zhang, Mingyi Hong, Ruoyu Sun, Zhi-Quan Luo:
When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work. NeurIPS 2021: 9167-9180 - 2020
- [c4]Jiawei Zhang, Songyang Ge, Tsung-Hui Chang
, Zhi-Quan Luo:
A Proximal Dual Consensus Method for Linearly Coupled Multi-Agent Non-Convex Optimization. ICASSP 2020: 5740-5744 - [c3]Linning Xu, Yijue Dai, Jiawei Zhang, Ceyao Zhang, Feng Yin:
Exact O(N2) Hyper-Parameter Optimization for Gaussian Process Regression. MLSP 2020: 1-6 - [c2]Jiawei Zhang, Peijun Xiao, Ruoyu Sun, Zhi-Quan Luo:
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems. NeurIPS 2020 - 2019
- [c1]Yue Xu, Feng Yin, Jiawei Zhang, Wenjun Xu, Shuguang Cui, Zhi-Quan Luo:
Scalable Gaussian Process Using Inexact Admm for Big Data. ICASSP 2019: 7495-7499
Informal and Other Publications
- 2024
- [i9]Jiancong Xiao, Jiawei Zhang, Zhi-Quan Luo, Asuman E. Ozdaglar:
Uniformly Stable Algorithms for Adversarial Training and Beyond. CoRR abs/2405.01817 (2024) - [i8]Kihyun Kim, Jiawei Zhang, Asuman E. Ozdaglar, Pablo A. Parrilo:
A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback. CoRR abs/2405.12421 (2024) - 2022
- [i7]Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang:
What is a Good Metric to Study Generalization of Minimax Learners? CoRR abs/2206.04502 (2022) - [i6]Jiawei Zhang, Yushun Zhang, Mingyi Hong, Ruoyu Sun, Zhi-Quan Luo:
When Expressivity Meets Trainability: Fewer than n Neurons Can Work. CoRR abs/2210.12001 (2022) - [i5]Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang:
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation. CoRR abs/2212.13861 (2022) - 2021
- [i4]Jiawei Zhang, Songyang Ge, Tsung-Hui Chang, Zhi-Quan Luo:
Decentralized Non-Convex Learning with Linearly Coupled Constraints. CoRR abs/2103.05378 (2021) - 2020
- [i3]Jiawei Zhang, Peijun Xiao, Ruoyu Sun, Zhi-Quan Luo:
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems. CoRR abs/2010.15768 (2020) - [i2]Zhiguo Wang, Jiawei Zhang, Tsung-Hui Chang, Jian Li, Zhi-Quan Luo:
Distributed Stochastic Consensus Optimization with Momentum for Nonconvex Nonsmooth Problems. CoRR abs/2011.05082 (2020) - 2019
- [i1]Linning Xu, Feng Yin, Jiawei Zhang, Zhi-Quan Luo, Shuguang Cui:
A General O(n2) Hyper-Parameter Optimization for Gaussian Process Regression with Cross-Validation and Non-linearly Constrained ADMM. CoRR abs/1906.02387 (2019)
Coauthor Index
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last updated on 2024-08-16 19:27 CEST by the dblp team
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