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ORCIDMeng Wang 0003
Person information
- affiliation: Rensselaer Polytechnic Institute, Troy, NY, USA
- affiliation (PhD 2012): Cornell University, Ithaca, NY, USA
Other persons with the same name
- Meng Wang — disambiguation page
- Meng Wang 0001
![[0000-0002-3094-7735]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-3094-7735")
— Hefei University of Technology, China (and 4 more) - Meng Wang 0002 — University of Bristol, UK (and 3 more)
- Meng Wang 0004 — Fujian Normal University, Key Lab of Network Security and Cryptography, Fuzhou, China
- Meng Wang 0005 — The Hong Kong Polytechnic University, Department of Computing, Hong Kong
- Meng Wang 0006 — South China University of Technology, Guangzhou, China
- Meng Wang 0007 — Stanford University, Department of Genetics, CA, USA (and 1 more)
- Meng Wang 0008 — Nankai University, Institute of Robotics and Automatic Information System, Tianjin, China
- Meng Wang 0009 — Tongji University, Shanghai, China (and 2 more)
- Meng Wang 0010 — Henan Normal University, School of Electronic and Electrical Engineering, Xinxiang, China (and 1 more)
- Meng Wang 0011 — China University of Geosciences, School of Geophysics and Information Technology, Beijing, China
- Meng Wang 0012 — Shaanxi Huanghe Group Co., Ltd., Xi'an, China
- Meng Wang 0013 — City University of Hong Kong, Department of Mechanical and Biomedical Engineering, Hong Kong (and 2 more)
- Meng Wang 0014 — Beijing University of Technology, Faculty of Information Technology, China
- Meng Wang 0015 — Xidian University, School of Computer Science and Technology, Xi'an, China
- Meng Wang 0016 — Zhejiang University, Hangzhou, China
- Meng Wang 0017 — City University of Hong Kong, Department of Computer Science (and 1 more)
- Meng Wang 0018 — Beijing University of Posts and Telecommunications, State Key Laboratory of Networking and Switching Technology, China
- Meng Wang 0019 — Tsinghua University, Department of Electrical Engineering, Beijing, China
- Meng Wang 0020 — TU Dresden, Institute of Traffic Telematics, Germany (and 1 more)
- Meng Wang 0021 — Hebei University, Cyberspace Security and Computer College, China (and 1 more)
- Meng Wang 0022 — Qufu Normal University, School of Geography and Tourism, Rizhao, China
- Meng Wang 0023 — Harbin University of Science and Technology, Department of Automation, China
- Meng Wang 0024 — Kunming University of Science and Technology, Faculty of Information Engineering and Automation / Yunnan Key Laboratory of Artificial Intelligence, China
- Meng Wang 0025 — Central University of Finance and Economics, School of Information, Beijing, China
- Meng Wang 0026 — Beijing University of Posts and Telecommunications, State Key Laboratory of Information Photonics and Optical Communications / School of Science, China
- Meng Wang 0027 — Jiangsu University of Science and Technology, School of Computer Science, Zhenjiang, China
- Meng Wang 0028 — Dalian Maritime University, College of Information Science and Technology, China
- Meng Wang 0029 — Northeastern University, Software College, Shenyang, China
- Meng Wang 0030 — Chang'an University, School of Information Engineering, Xi'an, China
- Meng Wang 0031 — Sun Yat-Sen University, School of Information Management, Guangzhou, China
- Meng Wang 0032 — East China Jiaotong University, School of Information Engineering, Nanchang, China
- Meng Wang 0033 — University of British Columbia, Vancouver, BC, Canada
- Meng Wang 0034 — Sun Yat-sen University, School of Intelligent Systems Engineering, Shenzhen, China
- Meng Wang 0035 — Army Engineering University of PLA, College of Communications Engineering, Nanjing, China
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2020 – today
- 2024
[c34]Heshan Devaka Fernando, Lisha Chen, Songtao Lu, Pin-Yu Chen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Gaowen Liu, Meng Wang, Tianyi Chen:
Variance Reduction Can Improve Trade-Off in Multi-Objective Learning. ICASSP 2024: 6975-6979- [c33]Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang:
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. ICML 2024 - [c32]Mohammed Nowaz Rabbani Chowdhury, Meng Wang, Kaoutar El Maghraoui, Naigang Wang, Pin-Yu Chen, Christopher D. Carothers:
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts. ICML 2024 - [c31]Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen:
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning? ICML 2024 - [c30]Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen:
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding. ICML 2024 - [c29]Hongkang Li, Meng Wang, Shuai Zhang, Sijia Liu, Pin-Yu Chen:
Learning on Transformers is Provable Low-Rank and Sparse: A One-layer Analysis. SAM 2024: 1-5 - [i30]Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen:
Training Nonlinear Transformers for Efficient In-Context Learning: A Theoretical Learning and Generalization Analysis. CoRR abs/2402.15607 (2024) - [i29]Hongkang Li, Shuai Zhang, Yihua Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen:
How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance. CoRR abs/2403.07310 (2024) - [i28]Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang:
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. CoRR abs/2405.15920 (2024) - [i27]Mohammed Nowaz Rabbani Chowdhury, Meng Wang, Kaoutar El Maghraoui, Naigang Wang, Pin-Yu Chen, Christopher D. Carothers:
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts. CoRR abs/2405.16646 (2024) - [i26]Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen:
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding. CoRR abs/2406.01977 (2024) - [i25]Hongkang Li, Meng Wang, Shuai Zhang, Sijia Liu, Pin-Yu Chen:
Learning on Transformers is Provable Low-Rank and Sparse: A One-layer Analysis. CoRR abs/2406.17167 (2024) - [i24]Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen:
Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis. CoRR abs/2410.02167 (2024) - 2023
- [c28]Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu:
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks. ICLR 2023 - [c27]Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen:
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity. ICLR 2023 - [c26]Mohammed Nowaz Rabbani Chowdhury, Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen:
Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks. ICML 2023: 6074-6114 - [c25]Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury:
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. NeurIPS 2023 - [i23]Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu:
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks. CoRR abs/2302.02922 (2023) - [i22]Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen:
A Theoretical Understanding of shallow Vision Transformers: Learning, Generalization, and Sample Complexity. CoRR abs/2302.06015 (2023) - [i21]Mohammed Nowaz Rabbani Chowdhury, Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen:
Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks. CoRR abs/2306.04073 (2023) - [i20]Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury:
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. CoRR abs/2310.16173 (2023) - 2022
- [j17]Ehsan Hallaji, Roozbeh Razavi-Far, Meng Wang, Mehrdad Saif, Bruce Fardanesh:
A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems. IEEE Trans. Inf. Forensics Secur. 17: 3934-3945 (2022) - [c24]Hongkang Li, Shuai Zhang, Meng Wang:
Learning and generalization of one-hidden-layer neural networks, going beyond standard Gaussian data. CISS 2022: 37-42 - [c23]Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong:
How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis. ICLR 2022 - [c22]Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong:
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling. ICML 2022: 13014-13051 - [i19]Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong:
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis. CoRR abs/2201.08514 (2022) - [i18]Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong:
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling. CoRR abs/2207.03584 (2022) - [i17]Hongkang Li, Shuai Zhang, Meng Wang:
Learning and generalization of one-hidden-layer neural networks, going beyond standard Gaussian data. CoRR abs/2207.03615 (2022) - [i16]Ehsan Hallaji, Roozbeh Razavi-Far, Meng Wang, Mehrdad Saif, Bruce Fardanesh:
A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems. CoRR abs/2210.06729 (2022) - 2021
- [j16]Shuai Zhang, Meng Wang, Jinjun Xiong, Sijia Liu, Pin-Yu Chen:
Improved Linear Convergence of Training CNNs With Generalizability Guarantees: A One-Hidden-Layer Case. IEEE Trans. Neural Networks Learn. Syst. 32(6): 2622-2635 (2021) - [c21]Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang:
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning. ICLR 2021 - [c20]Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong:
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks. NeurIPS 2021: 2707-2720 - [i15]Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang:
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning. CoRR abs/2102.10454 (2021) - [i14]Tianyi Chen, Meng Wang, Siyuan Gong, Yang Zhou, Bin Ran:
Connected and Automated Vehicle Distributed Control for On-ramp Merging Scenario: A Virtual Rotation Approach. CoRR abs/2103.15047 (2021) - [i13]Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong:
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks. CoRR abs/2110.05667 (2021) - 2020
- [j15]Ren Wang, Meng Wang, Jinjun Xiong:
Achieve data privacy and clustering accuracy simultaneously through quantized data recovery. EURASIP J. Adv. Signal Process. 2020(1): 22 (2020) - [j14]Ren Wang, Meng Wang, Jinjun Xiong:
Tensor recovery from noisy and multi-level quantized measurements. EURASIP J. Adv. Signal Process. 2020(1): 41 (2020) - [j13]Stavros Konstantinopoulos, Genevieve M. De Mijolla, Joe H. Chow, Hanoch Lev-Ari, Meng Wang:
Synchrophasor Missing Data Recovery via Data-Driven Filtering. IEEE Trans. Smart Grid 11(5): 4321-4330 (2020) - [c19]Ren Wang, Meng Wang, Jinjun Xiong:
Quantized Higher-Order Tensor Recovery by Exploring Low-Dimensional Structures. ACSSC 2020: 923-928 - [c18]Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong:
Guaranteed Convergence of Training Convolutional Neural Networks via Accelerated Gradient Descent. CISS 2020: 1-6 - [c17]Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong, Meng Wang:
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases. ECCV (23) 2020: 222-238 - [c16]Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong:
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case. ICML 2020: 11268-11277 - [i12]Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong:
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case. CoRR abs/2006.14117 (2020) - [i11]Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong, Meng Wang:
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases. CoRR abs/2007.15802 (2020)
2010 – 2019
- 2019
- [j12]Shuai Zhang, Meng Wang:
Correction of Corrupted Columns Through Fast Robust Hankel Matrix Completion. IEEE Trans. Signal Process. 67(10): 2580-2594 (2019) - [i10]Ren Wang, Meng Wang, Jinjun Xiong:
Tensor Recovery from Noisy and Multi-Level Quantized Measurements. CoRR abs/1912.02588 (2019) - 2018
- [j11]Shuai Zhang, Yingshuai Hao, Meng Wang, Joe H. Chow:
Multichannel Hankel Matrix Completion Through Nonconvex Optimization. IEEE J. Sel. Top. Signal Process. 12(4): 617-632 (2018) - [j10]Ren Wang, Meng Wang, Jinjun Xiong:
Data Recovery and Subspace Clustering From Quantized and Corrupted Measurements. IEEE J. Sel. Top. Signal Process. 12(6): 1547-1560 (2018) - [j9]Yingshuai Hao, Meng Wang, Joe H. Chow:
Likelihood Analysis of Cyber Data Attacks to Power Systems With Markov Decision Processes. IEEE Trans. Smart Grid 9(4): 3191-3202 (2018) - [j8]Pengzhi Gao, Ren Wang, Meng Wang, Joe H. Chow:
Low-Rank Matrix Recovery From Noisy, Quantized, and Erroneous Measurements. IEEE Trans. Signal Process. 66(11): 2918-2932 (2018) - [c15]Pengzhi Gao, Meng Wang:
Dynamic Matrix Recovery from Partially Observed and Erroneous Measurements. ICASSP 2018: 4089-4093 - [c14]Shuai Zhang, Meng Wang:
Correction of Simultaneous Bad Measurements by Exploiting the Low-rank Hankel Structure. ISIT 2018: 646-650 - 2017
- [j7]Pengzhi Gao, Meng Wang, Joe H. Chow, Matthew Berger, Lee M. Seversky:
Missing Data Recovery for High-Dimensional Signals With Nonlinear Low-Dimensional Structures. IEEE Trans. Signal Process. 65(20): 5421-5436 (2017) - [c13]Shuai Zhang, Yingshuai Hao, Meng Wang, Joe H. Chow:
Multi-Channel missing data recovery by exploiting the low-rank hankel structures. CAMSAP 2017: 1-5 - 2016
- [j6]Pengzhi Gao, Meng Wang, Joe H. Chow, Scott G. Ghiocel, Bruce Fardanesh, George Stefopoulos, Michael P. Razanousky:
Identification of Successive "Unobservable" Cyber Data Attacks in Power Systems Through Matrix Decomposition. IEEE Trans. Signal Process. 64(21): 5557-5570 (2016) - [c12]Pengzhi Gao, Ren Wang, Meng Wang, Joe H. Chow:
Low-rank matrix recovery from quantized and erroneous measurements: Accuracy-preserved data privatization in power grids. ACSSC 2016: 374-378 - [i9]Pengzhi Gao, Meng Wang, Joe H. Chow, Scott G. Ghiocel, Bruce Fardanesh, George Stefopoulos, Michael P. Razanousky:
Identification of Successive "Unobservable" Cyber Data Attacks in Power Systems Through Matrix Decomposition. CoRR abs/1607.04776 (2016) - 2015
- [j5]Meng Wang, Weiyu Xu, Enrique Mallada, Ao Tang:
Sparse Recovery With Graph Constraints. IEEE Trans. Inf. Theory 61(2): 1028-1044 (2015) - [c11]Yingshuai Hao, Meng Wang, Joe H. Chow:
Likelihood of cyber data injection attacks to power systems. GlobalSIP 2015: 657-661 - [c10]Pengzhi Gao, Meng Wang, Joe H. Chow, Matthew Berger, Lee M. Seversky:
Matrix completion with columns in union and sums of subspaces. GlobalSIP 2015: 785-789 - [c9]Meng Wang, Joe H. Chow, Pengzhi Gao, Xinyu Tony Jiang, Yu Xia, Scott G. Ghiocel, Bruce Fardanesh, George Stefopoulos, Yutaka Kokai, Nao Saito, Michael P. Razanousky:
A Low-Rank Matrix Approach for the Analysis of Large Amounts of Power System Synchrophasor Data. HICSS 2015: 2637-2644 - [i8]Yingshuai Hao, Meng Wang, Joe H. Chow:
Likelihood of Cyber Data Injection Attacks to Power Systems. CoRR abs/1512.05008 (2015) - 2014
- [c8]Meng Wang, Pengzhi Gao, Scott G. Ghiocel, Joe H. Chow, Bruce Fardanesh, George Stefopoulos, Michael P. Razanousky:
Identification of "unobservable" cyber data attacks on power grids. SmartGridComm 2014: 830-835 - 2013
- [j4]Weiyu Xu, Meng Wang, Jian-Feng Cai, Ao Tang:
Sparse Error Correction From Nonlinear Measurements With Applications in Bad Data Detection for Power Networks. IEEE Trans. Signal Process. 61(24): 6175-6187 (2013) - [c7]Meng Wang, Weiyu Xu, A. Robert Calderbank:
Compressed sensing with corrupted participants. ICASSP 2013: 4653-4657 - 2012
- [c6]Meng Wang, Weiyu Xu, Enrique Mallada, Ao Tang:
Sparse recovery with graph constraints: Fundamental limits and measurement construction. INFOCOM 2012: 1871-1879 - [i7]Meng Wang, Weiyu Xu, Enrique Mallada, Ao Tang:
Sparse Recovery with Graph Constraints. CoRR abs/1207.2829 (2012) - 2011
- [j3]Meng Wang, Weiyu Xu, Ao Tang:
On the Performance of Sparse Recovery Via lp-Minimization (0 <= p <= 1). IEEE Trans. Inf. Theory 57(11): 7255-7278 (2011) - [j2]Meng Wang, Chee Wei Tan, Weiyu Xu, Ao Tang:
Cost of Not Splitting in Routing: Characterization and Estimation. IEEE/ACM Trans. Netw. 19(6): 1849-1859 (2011) - [j1]Meng Wang, Weiyu Xu, Ao Tang:
A Unique "Nonnegative" Solution to an Underdetermined System: From Vectors to Matrices. IEEE Trans. Signal Process. 59(3): 1007-1016 (2011) - [c5]Weiyu Xu, Meng Wang, Enrique Mallada, Ao Tang:
Recent results on sparse recovery over graphs. ACSCC 2011: 413-417 - [c4]Weiyu Xu, Meng Wang, Ao Tang:
On state estimation with bad data detection. CDC/ECC 2011: 5989-5994 - [i6]Weiyu Xu, Meng Wang, Ao Tang:
On State Estimation with Bad Data Detection. CoRR abs/1105.0442 (2011) - [i5]Meng Wang, Weiyu Xu, Enrique Mallada, Ao Tang:
Sparse Recovery with Graph Constraints: Fundamental Limits and Measurement Construction. CoRR abs/1108.0443 (2011) - [i4]Weiyu Xu, Meng Wang, Ao Tang:
Sparse Recovery from Nonlinear Measurements with Applications in Bad Data Detection for Power Networks. CoRR abs/1112.6234 (2011) - 2010
- [c3]Meng Wang, Weiyu Xu, Ao Tang:
The limits of error correction with lp decoding. ISIT 2010: 749-753 - [i3]Meng Wang, Weiyu Xu, Ao Tang:
A Unique "Nonnegative" Solution to an Underdetermined System: from Vectors to Matrices. CoRR abs/1003.4778 (2010) - [i2]Meng Wang, Weiyu Xu, Ao Tang:
The Limits of Error Correction with lp Decoding. CoRR abs/1006.0277 (2010) - [i1]Meng Wang, Weiyu Xu, Ao Tang:
On the Performance of Sparse Recovery via L_p-minimization (0<=p <=1). CoRR abs/1011.5936 (2010)
2000 – 2009
- 2009
- [c2]Meng Wang, Ao Tang:
Conditions for a unique non-negative solution to an underdetermined system. Allerton 2009: 301-307 - [c1]Meng Wang, Chee Wei Tan, Ao Tang, Steven H. Low:
How Bad is Single-Path Routing. GLOBECOM 2009: 1-6
Coauthor Index
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