Conditions for a unique non-negative solution to an underdetermined system. - Meng Wang 003; Ao Tang (Allerton, 2009)

How Bad is Single-Path Routing. - Meng Wang 003; Chee Wei Tan 001; Ao Tang; Steven H. Low (GLOBECOM, 2009)

The limits of error correction with lp decoding. - Meng Wang 003; Weiyu Xu; Ao Tang (ISIT, 2010)

On the Performance of Sparse Recovery via L_p-minimization (0<=p <=1) - Meng Wang 003; Weiyu Xu; Ao Tang (CoRR, 2010)

Recent results on sparse recovery over graphs. - Weiyu Xu; Meng Wang 003; Enrique Mallada; Ao Tang (ACSCC, 2011)

On state estimation with bad data detection. - Weiyu Xu; Meng Wang 003; Ao Tang (CDC/ECC, 2011)

Sparse Recovery from Nonlinear Measurements with Applications in Bad Data Detection for Power Networks - Weiyu Xu; Meng Wang 003; Ao Tang (CoRR, 2011)

On the Performance of Sparse Recovery Via lp-Minimization (0 <= p <= 1). - Meng Wang 003; Weiyu Xu; Ao Tang (IEEE Trans. Inf. Theory, 2011)

Cost of Not Splitting in Routing: Characterization and Estimation. - Meng Wang 003; Chee Wei Tan 001; Weiyu Xu; Ao Tang (IEEE/ACM Trans. Netw., 2011)

A Unique "Nonnegative" Solution to an Underdetermined System: From Vectors to Matrices. - Meng Wang 003; Weiyu Xu; Ao Tang (IEEE Trans. Signal Process., 2011)

Sparse recovery with graph constraints: Fundamental limits and measurement construction. - Meng Wang 003; Weiyu Xu; Enrique Mallada; Ao Tang (INFOCOM, 2012)

Compressed sensing with corrupted participants. - Meng Wang 003; Weiyu Xu; A. Robert Calderbank (ICASSP, 2013)

Sparse Error Correction From Nonlinear Measurements With Applications in Bad Data Detection for Power Networks. - Weiyu Xu; Meng Wang 003; Jian-Feng Cai 001; Ao Tang (IEEE Trans. Signal Process., 2013)

Identification of "unobservable" cyber data attacks on power grids. - Meng Wang 003; Pengzhi Gao; Scott G. Ghiocel; Joe H. Chow; Bruce Fardanesh; George Stefopoulos; Michael P. Razanousky (SmartGridComm, 2014)

Matrix completion with columns in union and sums of subspaces. - Pengzhi Gao; Meng Wang 003; Joe H. Chow; Matthew Berger; Lee M. Seversky (GlobalSIP, 2015)

Likelihood of cyber data injection attacks to power systems. - Yingshuai Hao; Meng Wang 003; Joe H. Chow (GlobalSIP, 2015)

A Low-Rank Matrix Approach for the Analysis of Large Amounts of Power System Synchrophasor Data. - Meng Wang 003; Joe H. Chow; Pengzhi Gao; Xinyu Tony Jiang; Yu Xia; Scott G. Ghiocel; Bruce Fardanesh; George Stefopoulos; Yutaka Kokai; Nao Saito; Michael P. Razanousky (HICSS, 2015)

Sparse Recovery With Graph Constraints. - Meng Wang 003; Weiyu Xu; Enrique Mallada; Ao Tang (IEEE Trans. Inf. Theory, 2015)

Low-rank matrix recovery from quantized and erroneous measurements: Accuracy-preserved data privatization in power grids. - Pengzhi Gao; Ren Wang 008; Meng Wang 003; Joe H. Chow (ACSSC, 2016)

Identification of Successive "Unobservable" Cyber Data Attacks in Power Systems Through Matrix Decomposition. - Pengzhi Gao; Meng Wang 003; Joe H. Chow; Scott G. Ghiocel; Bruce Fardanesh; George Stefopoulos; Michael P. Razanousky (IEEE Trans. Signal Process., 2016)

Multi-Channel missing data recovery by exploiting the low-rank hankel structures. - Shuai Zhang 015; Yingshuai Hao; Meng Wang 003; Joe H. Chow (CAMSAP, 2017)

Missing Data Recovery for High-Dimensional Signals With Nonlinear Low-Dimensional Structures. - Pengzhi Gao; Meng Wang 003; Joe H. Chow; Matthew Berger; Lee M. Seversky (IEEE Trans. Signal Process., 2017)

Dynamic Matrix Recovery from Partially Observed and Erroneous Measurements. - Pengzhi Gao; Meng Wang 003 (ICASSP, 2018)

Correction of Simultaneous Bad Measurements by Exploiting the Low-rank Hankel Structure. - Shuai Zhang 015; Meng Wang 003 (ISIT, 2018)

Data Recovery and Subspace Clustering From Quantized and Corrupted Measurements. - Ren Wang 008; Meng Wang 003; Jinjun Xiong (IEEE J. Sel. Top. Signal Process., 2018)

Multichannel Hankel Matrix Completion Through Nonconvex Optimization. - Shuai Zhang 015; Yingshuai Hao; Meng Wang 003; Joe H. Chow (IEEE J. Sel. Top. Signal Process., 2018)

Likelihood Analysis of Cyber Data Attacks to Power Systems With Markov Decision Processes. - Yingshuai Hao; Meng Wang 003; Joe H. Chow (IEEE Trans. Smart Grid, 2018)

Low-Rank Matrix Recovery From Noisy, Quantized, and Erroneous Measurements. - Pengzhi Gao; Ren Wang 008; Meng Wang 003; Joe H. Chow (IEEE Trans. Signal Process., 2018)

Correction of Corrupted Columns Through Fast Robust Hankel Matrix Completion. - Shuai Zhang 015; Meng Wang 003 (IEEE Trans. Signal Process., 2019)

Quantized Higher-Order Tensor Recovery by Exploring Low-Dimensional Structures. - Ren Wang 008; Meng Wang 003; Jinjun Xiong (ACSSC, 2020)

Guaranteed Convergence of Training Convolutional Neural Networks via Accelerated Gradient Descent. - Shuai Zhang 015; Meng Wang 003; Sijia Liu 001; Pin-Yu Chen; Jinjun Xiong (CISS, 2020)

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases. - Ren Wang 008; Gaoyuan Zhang; Sijia Liu 001; Pin-Yu Chen; Jinjun Xiong; Meng Wang 003 (ECCV (23), 2020)

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case. - Shuai Zhang 015; Meng Wang 003; Sijia Liu 001; Pin-Yu Chen; Jinjun Xiong (ICML, 2020)

Achieve data privacy and clustering accuracy simultaneously through quantized data recovery. - Ren Wang 008; Meng Wang 003; Jinjun Xiong (EURASIP J. Adv. Signal Process., 2020)

Tensor recovery from noisy and multi-level quantized measurements. - Ren Wang 008; Meng Wang 003; Jinjun Xiong (EURASIP J. Adv. Signal Process., 2020)

Synchrophasor Missing Data Recovery via Data-Driven Filtering. - Stavros Konstantinopoulos; Genevieve M. De Mijolla; Joe H. Chow; Hanoch Lev-Ari; Meng Wang 003 (IEEE Trans. Smart Grid, 2020)

On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning. - Ren Wang 008; Kaidi Xu; Sijia Liu 001; Pin-Yu Chen; Tsui-Wei Weng; Chuang Gan 001; Meng Wang 003 (ICLR, 2021)

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks. - Shuai Zhang 015; Meng Wang 003; Sijia Liu 001; Pin-Yu Chen; Jinjun Xiong (NeurIPS, 2021)

Connected and Automated Vehicle Distributed Control for On-ramp Merging Scenario: A Virtual Rotation Approach. - Tianyi Chen; Meng Wang 003; Siyuan Gong; Yang Zhou; Bin Ran (CoRR, 2021)

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks. - Shuai Zhang 015; Meng Wang 003; Sijia Liu 001; Pin-Yu Chen; Jinjun Xiong (CoRR, 2021)

Improved Linear Convergence of Training CNNs With Generalizability Guarantees: A One-Hidden-Layer Case. - Shuai Zhang 015; Meng Wang 003; Jinjun Xiong; Sijia Liu 001; Pin-Yu Chen (IEEE Trans. Neural Networks Learn. Syst., 2021)

Learning and generalization of one-hidden-layer neural networks, going beyond standard Gaussian data. - Hongkang Li; Shuai Zhang 015; Meng Wang 003 (CISS, 2022)

How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis. - Shuai Zhang 015; Meng Wang 003; Sijia Liu 001; Pin-Yu Chen; Jinjun Xiong (ICLR, 2022)

Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling. - Hongkang Li; Meng Wang 003; Sijia Liu 001; Pin-Yu Chen; Jinjun Xiong (ICML, 2022)

How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis. - Shuai Zhang 015; Meng Wang 003; Sijia Liu 001; Pin-Yu Chen; Jinjun Xiong (CoRR, 2022)

A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems. - Ehsan Hallaji; Roozbeh Razavi-Far; Meng Wang 003; Mehrdad Saif; Bruce Fardanesh (IEEE Trans. Inf. Forensics Secur., 2022)

Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks. - Shuai Zhang 015; Meng Wang 003; Pin-Yu Chen; Sijia Liu 001; Songtao Lu; Miao Liu 001 (ICLR, 2023)

A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity. - Hongkang Li; Meng Wang 003; Sijia Liu 001; Pin-Yu Chen (ICLR, 2023)

Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks. - Mohammed Nowaz Rabbani Chowdhury; Shuai Zhang 015; Meng Wang 003; Sijia Liu 001; Pin-Yu Chen (ICML, 2023)

On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. - Shuai Zhang 015; Hongkang Li; Meng Wang 003; Miao Liu 001; Pin-Yu Chen; Songtao Lu; Sijia Liu 001; Keerthiram Murugesan; Subhajit Chaudhury (NeurIPS, 2023)

Variance Reduction Can Improve Trade-Off in Multi-Objective Learning. - Heshan Devaka Fernando; Lisha Chen; Songtao Lu; Pin-Yu Chen; Miao Liu 001; Subhajit Chaudhury; Keerthiram Murugesan; Gaowen Liu; Meng Wang 003; Tianyi Chen (ICASSP, 2024)

SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. - Shuai Zhang 015; Heshan Devaka Fernando; Miao Liu 001; Keerthiram Murugesan; Songtao Lu; Pin-Yu Chen; Tianyi Chen; Meng Wang 003 (ICML, 2024)

A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts. - Mohammed Nowaz Rabbani Chowdhury; Meng Wang 003; Kaoutar El Maghraoui; Naigang Wang; Pin-Yu Chen; Christopher D. Carothers (ICML, 2024)

How Do Nonlinear Transformers Learn and Generalize in In-Context Learning? - Hongkang Li; Meng Wang 003; Songtao Lu; Xiaodong Cui; Pin-Yu Chen (ICML, 2024)

What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding. - Hongkang Li; Meng Wang 003; Tengfei Ma 001; Sijia Liu 001; Zaixi Zhang; Pin-Yu Chen (ICML, 2024)

Learning on Transformers is Provable Low-Rank and Sparse: A One-layer Analysis. - Hongkang Li; Meng Wang 003; Shuai Zhang 015; Sijia Liu 001; Pin-Yu Chen (SAM, 2024)

Training Nonlinear Transformers for Efficient In-Context Learning: A Theoretical Learning and Generalization Analysis. - Hongkang Li; Meng Wang 003; Songtao Lu; Xiaodong Cui; Pin-Yu Chen (CoRR, 2024)

How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance. - Hongkang Li; Shuai Zhang 015; Yihua Zhang; Meng Wang 003; Sijia Liu 001; Pin-Yu Chen (CoRR, 2024)

Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis. - Hongkang Li; Meng Wang 003; Songtao Lu; Xiaodong Cui; Pin-Yu Chen (CoRR, 2024)

When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers. - Hongkang Li; Yihua Zhang; Shuai Zhang 015; Pin-Yu Chen; Sijia Liu 001; Meng Wang 003 (ICLR, 2025)