Meng Wang

Orcid: 0000-0003-0928-9691

Affiliations:
  • Rensselaer Polytechnic Institute, Troy, NY, USA
  • Cornell University, Ithaca, NY, USA (PhD 2012)


According to our database1, Meng Wang authored at least 59 papers between 2009 and 2024.

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Bibliography

2024
Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis.
CoRR, 2024

How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance.
CoRR, 2024

Training Nonlinear Transformers for Efficient In-Context Learning: A Theoretical Learning and Generalization Analysis.
CoRR, 2024

Learning on Transformers is Provable Low-Rank and Sparse: A One-layer Analysis.
Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024

What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Variance Reduction Can Improve Trade-Off in Multi-Objective Learning.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems.
IEEE Trans. Inf. Forensics Secur., 2022

How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis.
CoRR, 2022

Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling.
Proceedings of the International Conference on Machine Learning, 2022

How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning and generalization of one-hidden-layer neural networks, going beyond standard Gaussian data.
Proceedings of the 56th Annual Conference on Information Sciences and Systems, 2022

2021
Improved Linear Convergence of Training CNNs With Generalizability Guarantees: A One-Hidden-Layer Case.
IEEE Trans. Neural Networks Learn. Syst., 2021

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks.
CoRR, 2021

Connected and Automated Vehicle Distributed Control for On-ramp Merging Scenario: A Virtual Rotation Approach.
CoRR, 2021

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Synchrophasor Missing Data Recovery via Data-Driven Filtering.
IEEE Trans. Smart Grid, 2020

Tensor recovery from noisy and multi-level quantized measurements.
EURASIP J. Adv. Signal Process., 2020

Achieve data privacy and clustering accuracy simultaneously through quantized data recovery.
EURASIP J. Adv. Signal Process., 2020

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case.
Proceedings of the 37th International Conference on Machine Learning, 2020

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases.
Proceedings of the Computer Vision - ECCV 2020, 2020

Guaranteed Convergence of Training Convolutional Neural Networks via Accelerated Gradient Descent.
Proceedings of the 54th Annual Conference on Information Sciences and Systems, 2020

Quantized Higher-Order Tensor Recovery by Exploring Low-Dimensional Structures.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019
Correction of Corrupted Columns Through Fast Robust Hankel Matrix Completion.
IEEE Trans. Signal Process., 2019

2018
Low-Rank Matrix Recovery From Noisy, Quantized, and Erroneous Measurements.
IEEE Trans. Signal Process., 2018

Likelihood Analysis of Cyber Data Attacks to Power Systems With Markov Decision Processes.
IEEE Trans. Smart Grid, 2018

Multichannel Hankel Matrix Completion Through Nonconvex Optimization.
IEEE J. Sel. Top. Signal Process., 2018

Data Recovery and Subspace Clustering From Quantized and Corrupted Measurements.
IEEE J. Sel. Top. Signal Process., 2018

Correction of Simultaneous Bad Measurements by Exploiting the Low-rank Hankel Structure.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Dynamic Matrix Recovery from Partially Observed and Erroneous Measurements.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017
Missing Data Recovery for High-Dimensional Signals With Nonlinear Low-Dimensional Structures.
IEEE Trans. Signal Process., 2017

Multi-Channel missing data recovery by exploiting the low-rank hankel structures.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2016
Identification of Successive "Unobservable" Cyber Data Attacks in Power Systems Through Matrix Decomposition.
IEEE Trans. Signal Process., 2016

Low-rank matrix recovery from quantized and erroneous measurements: Accuracy-preserved data privatization in power grids.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
Sparse Recovery With Graph Constraints.
IEEE Trans. Inf. Theory, 2015

A Low-Rank Matrix Approach for the Analysis of Large Amounts of Power System Synchrophasor Data.
Proceedings of the 48th Hawaii International Conference on System Sciences, 2015

Likelihood of cyber data injection attacks to power systems.
Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015

Matrix completion with columns in union and sums of subspaces.
Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015

2014
Identification of "unobservable" cyber data attacks on power grids.
Proceedings of the 2014 IEEE International Conference on Smart Grid Communications, 2014

2013
Sparse Error Correction From Nonlinear Measurements With Applications in Bad Data Detection for Power Networks.
IEEE Trans. Signal Process., 2013

Compressed sensing with corrupted participants.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Sparse recovery with graph constraints: Fundamental limits and measurement construction.
Proceedings of the IEEE INFOCOM 2012, Orlando, FL, USA, March 25-30, 2012, 2012

2011
A Unique "Nonnegative" Solution to an Underdetermined System: From Vectors to Matrices.
IEEE Trans. Signal Process., 2011

Cost of Not Splitting in Routing: Characterization and Estimation.
IEEE/ACM Trans. Netw., 2011

On the Performance of Sparse Recovery Via l<sub>p</sub>-Minimization (0 <= p <= 1).
IEEE Trans. Inf. Theory, 2011

Sparse Recovery from Nonlinear Measurements with Applications in Bad Data Detection for Power Networks
CoRR, 2011

On state estimation with bad data detection.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

Recent results on sparse recovery over graphs.
Proceedings of the Conference Record of the Forty Fifth Asilomar Conference on Signals, 2011

2010
On the Performance of Sparse Recovery via L_p-minimization (0<=p <=1)
CoRR, 2010

The limits of error correction with lp decoding.
Proceedings of the IEEE International Symposium on Information Theory, 2010

2009
How Bad is Single-Path Routing.
Proceedings of the Global Communications Conference, 2009. GLOBECOM 2009, Honolulu, Hawaii, USA, 30 November, 2009

Conditions for a unique non-negative solution to an underdetermined system.
Proceedings of the 47th Annual Allerton Conference on Communication, 2009


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