Mingyi Hong

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 249

Top Venues

CoRR

ICASSP

IEEE Trans. Signal Process.

NeurIPS

Publications

Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. CoRR (2024)
Ruichen Jiang, Parameswaran Raman, Shoham Sabach, Aryan Mokhtari, Mingyi Hong, Volkan Cevher
Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate. CoRR (2024)
Junyu Zhang, Mingyi Hong
First-Order Algorithms Without Lipschitz Gradient: A Sequential Local Optimization Approach. INFORMS J. Optim. 6 (2) (2024)
Xun Xian, Ganghua Wang, Xuan Bi, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding
RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees. CoRR (2024)
Andi Han, Jiaxiang Li, Wei Huang, Mingyi Hong, Akiko Takeda, Pratik Jawanpuria, Bamdev Mishra
SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining. CoRR (2024)
Chenliang Li, Siliang Zeng, Zeyi Liao, Jiaxiang Li, Dongyeop Kang, Alfredo García, Mingyi Hong
Joint Demonstration and Preference Learning Improves Policy Alignment with Human Feedback. CoRR (2024)
Jiaxiang Li, Siliang Zeng, Hoi-To Wai, Chenliang Li, Alfredo García, Mingyi Hong
Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment. CoRR (2024)
Ya-Feng Liu, Tsung-Hui Chang, Mingyi Hong, Zheyu Wu, Anthony Man-Cho So, Eduard A. Jorswieck, Wei Yu
A Survey of Advances in Optimization Methods for Wireless Communication System Design. CoRR (2024)
Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, Sijia Liu
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models. CoRR (2024)
Shixiang Chen, Alfredo García, Mingyi Hong, Shahin Shahrampour
On the Local Linear Rate of Consensus on the Stiefel Manifold. IEEE Trans. Autom. Control. 69 (4) (2024)
Yihua Zhang, Prashant Khanduri, Ioannis C. Tsaknakis, Yuguang Yao, Mingyi Hong, Sijia Liu
An Introduction to Bilevel Optimization: Foundations and applications in signal processing and machine learning. IEEE Signal Process. Mag. 41 (1) (2024)
Ruichen Jiang, Parameswaran Raman, Shoham Sabach, Aryan Mokhtari, Mingyi Hong, Volkan Cevher
Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate. AISTATS (2024)
Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis
Pre-training Differentially Private Models with Limited Public Data. CoRR (2024)
Chung-Yiu Yau, Hoi-To Wai, Parameswaran Raman, Soumajyoti Sarkar, Mingyi Hong
: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence. CoRR (2024)
Jiaxiang Li, Xuxing Chen, Shiqian Ma, Mingyi Hong
Problem-Parameter-Free Decentralized Nonconvex Stochastic Optimization. CoRR (2024)
Zhiwei Tang, Jiangweizhi Peng, Jiasheng Tang, Mingyi Hong, Fan Wang, Tsung-Hui Chang
Tuning-Free Alignment of Diffusion Models with Direct Noise Optimization. CoRR (2024)
Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher
MADA: Meta-Adaptive Optimizers through hyper-gradient Descent. CoRR (2024)
Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu
What Is Missing in IRM Training and Evaluation? Challenges and Solutions. ICLR (2023)
Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu
What Is Missing in IRM Training and Evaluation? Challenges and Solutions. CoRR (2023)
Zhanpeng Zeng, Cole Hawkins, Mingyi Hong, Aston Zhang, Nikolaos Pappas, Vikas Singh, Shuai Zheng
Vcc: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens. CoRR (2023)
Ioannis C. Tsaknakis, Mingyi Hong, Shuzhong Zhang
Minimax Problems with Coupled Linear Constraints: Computational Complexity and Duality. SIAM J. Optim. 33 (4) (2023)
Ran Wei, Siliang Zeng, Chenliang Li, Alfredo Garcia, Anthony D. McDonald, Mingyi Hong
A Bayesian Approach to Robust Inverse Reinforcement Learning. CoRL (2023)
Sagar Shrestha, Xiao Fu, Mingyi Hong
Optimal Solutions for Joint Beamforming and Antenna Selection: From Branch and Bound to Graph Neural Imitation Learning. IEEE Trans. Signal Process. 71 (2023)
Xinwei Zhang, Zhiqi Bu, Zhiwei Steven Wu, Mingyi Hong
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach. CoRR (2023)
Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong
When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning. NeurIPS (2023)
Minghe Zhu, Tsung-Hui Chang, Mingyi Hong
Learning to Beamform in Heterogeneous Massive MIMO Networks. IEEE Trans. Wirel. Commun. 22 (7) (2023)
Ran Wei, Siliang Zeng, Chenliang Li, Alfredo Garcia, Anthony D. McDonald, Mingyi Hong
A Bayesian Approach to Robust Inverse Reinforcement Learning. CoRR (2023)
Xinwei Zhang, Mingyi Hong, Nicola Elia
Understanding a Class of Decentralized and Federated Optimization Algorithms: A Multirate Feedback Control Perspective. SIAM J. Optim. 33 (2) (2023)
Junyu Zhang, Mengdi Wang, Mingyi Hong, Shuzhong Zhang
Primal-Dual First-Order Methods for Affinely Constrained Multi-block Saddle Point Problems. SIAM J. Optim. 33 (2) (2023)
Bingqing Song, Zhicheng Zhou, Chenliang Li, Dongning Guo, Xiao Fu, Mingyi Hong
Transformer Based Approach for Wireless Resource Allocation Problems Involving Mixed Discrete and Continuous Variables. SPAWC (2023)
Ganghua Wang, Xun Xian, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding
Demystifying Poisoning Backdoor Attacks from a Statistical Perspective. CoRR (2023)
Han Shen, Kaiqing Zhang, Mingyi Hong, Tianyi Chen
Towards Understanding Asynchronous Advantage Actor-Critic: Convergence and Linear Speedup. IEEE Trans. Signal Process. 71 (2023)
Xinwei Zhang, Mingyi Hong, Jie Chen
GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data. CoRR (2023)
Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning. CoRR (2023)
Zhanpeng Zeng, Cole Hawkins, Mingyi Hong, Aston Zhang, Nikolaos Pappas, Vikas Singh, Shuai Zheng
VCC: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens. NeurIPS (2023)
Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning. NeurIPS (2023)
Ioannis C. Tsaknakis, Prashant Khanduri, Mingyi Hong
An Implicit Gradient Method for Constrained Bilevel Problems Using Barrier Approximation. ICASSP (2023)
Sagar Shrestha, Xiao Fu, Mingyi Hong
Towards Efficient and Optimal Joint Beamforming and Antenna Selection: A Machine Learning Approach. ICASSP (2023)
Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding
A Unified Detection Framework for Inference-Stage Backdoor Defenses. NeurIPS (2023)
Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding
Understanding Backdoor Attacks through the Adaptability Hypothesis. ICML (2023)
Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
A Two-Timescale Stochastic Algorithm Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic. SIAM J. Optim. 33 (1) (2023)
Bingqing Song, Prashant Khanduri, Xinwei Zhang, Jinfeng Yi, Mingyi Hong
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks. ICML (2023)
Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong
Understanding Expertise through Demonstrations: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning. CoRR (2023)
Yihua Zhang, Prashant Khanduri, Ioannis C. Tsaknakis, Yuguang Yao, Mingyi Hong, Sijia Liu
An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning. CoRR (2023)
Prashant Khanduri, Ioannis C. Tsaknakis, Yihua Zhang, Jia Liu, Sijia Liu, Jiawei Zhang, Mingyi Hong
Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach. ICML (2023)
Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi-To Wai, Sijia Liu
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach. ICLR (2022)
Sagar Shrestha, Xiao Fu, Mingyi Hong
Deep Spectrum Cartography: Completing Radio Map Tensors Using Learned Neural Models. IEEE Trans. Signal Process. 70 (2022)
Junyu Zhang, Mingyi Hong, Shuzhong Zhang
On lower iteration complexity bounds for the convex concave saddle point problems. Math. Program. 194 (1) (2022)
Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Steven Wu, Jinfeng Yi
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. ICML (2022)
Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Nicola Elia
A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms. ICML (2022)
Siliang Zeng, Tianyi Chen, Alfredo Garcia, Mingyi Hong
Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees. L4DC (2022)
Jiawei Zhang, Yushun Zhang, Mingyi Hong, Ruoyu Sun, Zhi-Quan Luo
When Expressivity Meets Trainability: Fewer than n Neurons Can Work. CoRR (2022)
Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu
Advancing Model Pruning via Bi-level Optimization. CoRR (2022)
Siliang Zeng, Mingyi Hong, Alfredo Garcia
Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees. CoRR (2022)
Sagar Shrestha, Xiao Fu, Mingyi Hong
Optimal Solutions for Joint Beamforming and Antenna Selection: From Branch and Bound to Machine Learning. CoRR (2022)
Xun Xian, Mingyi Hong, Jie Ding
Mismatched Supervised Learning. ICASSP (2022)
Yang Liu, Xinwei Zhang, Yan Kang, Liping Li, Tianjian Chen, Mingyi Hong, Qiang Yang
FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features. IEEE Trans. Signal Process. 70 (2022)
Ioannis C. Tsaknakis, Prashant Khanduri, Mingyi Hong
An Implicit Gradient-Type Method for Linearly Constrained Bilevel Problems. ICASSP (2022)
Wenqiang Pu, Shahana Ibrahim, Xiao Fu, Mingyi Hong
Stochastic Mirror Descent for Low-Rank Tensor Decomposition Under Non-Euclidean Losses. IEEE Trans. Signal Process. 70 (2022)
Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong
Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees. CoRR (2022)
Xinran Wang, Jiawei Zhang, Mingyi Hong, Yuhong Yang, Jie Ding
Parallel Assisted Learning. IEEE Trans. Signal Process. 70 (2022)
Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective. CoRR (2022)
Yihua Zhang, Guanhua Zhang, Prashant Khanduri, Mingyi Hong, Shiyu Chang, Sijia Liu
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization. ICML (2022)
Ioannis C. Tsaknakis, Bhavya Kailkhura, Sijia Liu, Donald Loveland, James Diffenderfer, Anna Maria Hiszpanski, Mingyi Hong
Zeroth-Order SciML: Non-intrusive Integration of Scientific Software with Deep Learning. CoRR (2022)
Xinwei Zhang, Mingyi Hong, Nicola Elia
Understanding A Class of Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective. CoRR (2022)
Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark S. Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, Mingyi Hong
A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization. NeurIPS (2022)
Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale. CoRR (2022)
Xun Xian, Mingyi Hong, Jie Ding
Understanding Model Extraction Games. TPS-ISA (2022)
Mingyi Hong, Siliang Zeng, Junyu Zhang, Haoran Sun
On the Divergence of Decentralized Nonconvex Optimization. SIAM J. Optim. 32 (4) (2022)
Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu
Advancing Model Pruning via Bi-level Optimization. NeurIPS (2022)
Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Nie, Zhaoran Wang
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence. NeurIPS (2022)
Bingqing Song, Ioannis C. Tsaknakis, Chung-Yiu Yau, Hoi-To Wai, Mingyi Hong
Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity. NeurIPS (2022)
Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong
Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees. NeurIPS (2022)
Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective. ICLR (2022)
Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu
Distributed adversarial training to robustify deep neural networks at scale. UAI (2022)
Haoran Sun, Wenqiang Pu, Xiao Fu, Tsung-Hui Chang, Mingyi Hong
Learning to Continuously Optimize Wireless Resource in a Dynamic Environment: A Bilevel Optimization Perspective. IEEE Trans. Signal Process. 70 (2022)
Xun Xian, Mingyi Hong, Jie Ding
A Framework for Understanding Model Extraction Attack and Defense. CoRR (2022)
Lingyun Zhou, Xihan Chen, Mingyi Hong, Shi Jin, Qingjiang Shi
Efficient Resource Allocation for Multi-UAV Communication Against Adjacent and Co-Channel Interference. IEEE Trans. Veh. Technol. 70 (10) (2021)
Jiawei Zhang, Yushun Zhang, Mingyi Hong, Ruoyu Sun, Zhi-Quan Luo
When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work. NeurIPS (2021)
Chi Zhang, Jinghan Jia, Burhaneddin Yaman, Steen Moeller, Sijia Liu, Mingyi Hong, Mehmet Akçakaya
On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations. CoRR (2021)
Junyu Zhang, Mingyi Hong, Mengdi Wang, Shuzhong Zhang
Generalization Bounds for Stochastic Saddle Point Problems. AISTATS (2021)
Kexin Tang, Nuowen Kan, Junni Zou, Chenglin Li, Xiao Fu, Mingyi Hong, Hongkai Xiong
Multi-User Adaptive Video Delivery Over Wireless Networks: A Physical Layer Resource-Aware Deep Reinforcement Learning Approach. IEEE Trans. Circuits Syst. Video Technol. 31 (2) (2021)
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour
Decentralized Riemannian Gradient Descent on the Stiefel Manifold. CoRR (2021)
Sagar Shrestha, Xiao Fu, Mingyi Hong
Deep Generative Model Learning For Blind Spectrum Cartography with NMF-Based Radio Map Disaggregation. ICASSP (2021)
Bingqing Song, Haoran Sun, Wenqiang Pu, Sijia Liu, Mingyi Hong
To Supervise or Not to Supervise: How to Effectively Learn Wireless Interference Management Models? SPAWC (2021)
Wenqiang Pu, Shahana Ibrahim, Xiao Fu, Mingyi Hong
Fiber-Sampled Stochastic Mirror Descent for Tensor Decomposition with β-Divergence. ICASSP (2021)
Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. NeurIPS (2021)
Songtao Lu, Jason D. Lee, Meisam Razaviyayn, Mingyi Hong
Linearized ADMM Converges to Second-Order Stationary Points for Non-Convex Problems. IEEE Trans. Signal Process. 69 (2021)
Sagar Shrestha, Xiao Fu, Mingyi Hong
Deep Spectrum Cartography: Completing Radio Map Tensors Using Learned Neural Models. CoRR (2021)
Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Jinfeng Yi
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. CoRR (2021)
Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization. CoRR (2021)
Haoran Sun, Wenqiang Pu, Minghe Zhu, Xiao Fu, Tsung-Hui Chang, Mingyi Hong
Learning to Continuously Optimize Wireless Resource in Episodically Dynamic Environment. ICASSP (2021)
Naichen Shi, Dawei Li, Mingyi Hong, Ruoyu Sun
RMSprop converges with proper hyper-parameter. ICLR (2021)
Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Wotao Yin, Yang Liu
FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data. IEEE Trans. Signal Process. 69 (2021)
Yijian Zhang, Emiliano Dall'Anese, Mingyi Hong
Online Proximal-ADMM for Time-Varying Constrained Convex Optimization. IEEE Trans. Signal Inf. Process. over Networks 7 (2021)
Yihua Zhang, Guanhua Zhang, Prashant Khanduri, Mingyi Hong, Shiyu Chang, Sijia Liu
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization. CoRR (2021)
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour
Decentralized Riemannian Gradient Descent on the Stiefel Manifold. ICML (2021)
Chi Zhang, Jinghan Jia, Burhaneddin Yaman, Steen Moeller, Sijia Liu, Mingyi Hong, Mehmet Akçakaya
Instabilities in Conventional Multi-Coil MRI Reconstruction with Small Adversarial Perturbations. ACSCC (2021)
Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum. NeurIPS (2021)
Ioannis C. Tsaknakis, Mingyi Hong
Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda Function. AISTATS (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mingyi Hong