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Mingyi Hong 0001
Person information
- affiliation: University of Minnesota, Department of Electrical and Computer Engineering, Minneapolis , MN, USA
- affiliation: Iowa State University, Department of Industrial and Manufacturing Systems Engineering, Ames, IA, USA
- affiliation (PhD 2011): University of Virginia, Charlottesville, VA, USA
Other persons with the same name
- Ming-Yi Hong 0002 (aka: Mingyi Hong 0002) — National Taiwan University, Graduate Program of Data Science, Taipei, Taiwan (and 1 more)
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2020 – today
- 2024
- [j85]Junyu Zhang
, Mingyi Hong
:
First-Order Algorithms Without Lipschitz Gradient: A Sequential Local Optimization Approach. INFORMS J. Optim. 6(2): 118-136 (2024) - [j84]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): 38-59 (2024) - [j83]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): 2324-2339 (2024) - [j82]Xinwei Zhang, Mingyi Hong, Jie Chen:
GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data. Trans. Mach. Learn. Res. 2024 (2024) - [j81]Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen:
Hybrid Federated Learning for Feature & Sample Heterogeneity: Algorithms and Implementation. Trans. Mach. Learn. Res. 2024 (2024) - [c135]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: 4411-4419 - [c134]Wenqiang Pu, Jiawei Zhang, Rui Zhou, Xiao Fu, Mingyi Hong:
A Smoothed Bregman Proximal Gradient Algorithm for Decentralized Nonconvex Optimization. ICASSP 2024: 8911-8915 - [c133]Ganghua Wang, Xun Xian, Ashish Kundu, Jayanth Srinivasa, Xuan Bi, Mingyi Hong, Jie Ding:
Demystifying Poisoning Backdoor Attacks from a Statistical Perspective. ICLR 2024 - [c132]Xinwei Zhang, Zhiqi Bu, Steven Wu, Mingyi Hong:
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach. ICLR 2024 - [c131]Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher:
MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent. ICML 2024 - [c130]Chung-Yiu Yau, Hoi-To Wai, Parameswaran Raman, Soumajyoti Sarkar, Mingyi Hong:
EMC2: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence. ICML 2024 - [c129]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. ICML 2024 - [c128]Toygan Kilic, Jürgen Herrler, Patrick Liebig, Ömer Burak Demirel, Armin M. Nagel, Mingyi Hong, Georgios B. Giannakis, Kâmil Ugurbil, Mehmet Akçakaya:
Towards Fast Hard-Constrained Parallel Transmit Design in Ultrahigh Field MRI with Physics-Driven Neural Networks. ISBI 2024: 1-5 - [i113]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 abs/2401.03058 (2024) - [i112]Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher:
MADA: Meta-Adaptive Optimizers through hyper-gradient Descent. CoRR abs/2401.08893 (2024) - [i111]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 abs/2401.12025 (2024) - [i110]Jiaxiang Li, Xuxing Chen, Shiqian Ma, Mingyi Hong:
Problem-Parameter-Free Decentralized Nonconvex Stochastic Optimization. CoRR abs/2402.08821 (2024) - [i109]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 abs/2402.11592 (2024) - [i108]Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis:
Pre-training Differentially Private Models with Limited Public Data. CoRR abs/2402.18752 (2024) - [i107]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 abs/2403.18774 (2024) - [i106]Chung-Yiu Yau, Hoi-To Wai, Parameswaran Raman, Soumajyoti Sarkar, Mingyi Hong:
EMC2: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence. CoRR abs/2404.10575 (2024) - [i105]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 abs/2405.15234 (2024) - [i104]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 abs/2405.17888 (2024) - [i103]Zhiwei Tang, Jiangweizhi Peng, Jiasheng Tang, Mingyi Hong, Fan Wang, Tsung-Hui Chang:
Tuning-Free Alignment of Diffusion Models with Direct Noise Optimization. CoRR abs/2405.18881 (2024) - [i102]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 abs/2406.02214 (2024) - [i101]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 abs/2406.06874 (2024) - 2023
- [j80]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): 147-180 (2023) - [j79]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): 652-683 (2023) - [j78]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): 1035-1060 (2023) - [j77]Ioannis C. Tsaknakis, Mingyi Hong, Shuzhong Zhang
:
Minimax Problems with Coupled Linear Constraints: Computational Complexity and Duality. SIAM J. Optim. 33(4): 2675-2702 (2023) - [j76]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: 831-846 (2023) - [j75]Han Shen
, Kaiqing Zhang, Mingyi Hong
, Tianyi Chen
:
Towards Understanding Asynchronous Advantage Actor-Critic: Convergence and Linear Speedup. IEEE Trans. Signal Process. 71: 2579-2594 (2023) - [j74]Minghe Zhu
, Tsung-Hui Chang
, Mingyi Hong
:
Learning to Beamform in Heterogeneous Massive MIMO Networks. IEEE Trans. Wirel. Commun. 22(7): 4901-4915 (2023) - [c127]Ran Wei, Siliang Zeng, Chenliang Li, Alfredo García, Anthony D. McDonald, Mingyi Hong:
A Bayesian Approach to Robust Inverse Reinforcement Learning. CoRL 2023: 2304-2322 - [c126]Sagar Shrestha, Xiao Fu, Mingyi Hong:
Towards Efficient and Optimal Joint Beamforming and Antenna Selection: A Machine Learning Approach. ICASSP 2023: 1-5 - [c125]Ioannis C. Tsaknakis, Prashant Khanduri, Mingyi Hong:
An Implicit Gradient Method for Constrained Bilevel Problems Using Barrier Approximation. ICASSP 2023: 1-5 - [c124]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 - [c123]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: 16291-16325 - [c122]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: 32304-32330 - [c121]Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding:
Understanding Backdoor Attacks through the Adaptability Hypothesis. ICML 2023: 37952-37976 - [c120]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 - [c119]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 - [c118]Siliang Zeng, Chenliang Li, Alfredo García, Mingyi Hong:
When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning. NeurIPS 2023 - [c117]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 - [c116]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: 636-640 - [i100]Siliang Zeng, Chenliang Li, Alfredo García, Mingyi Hong:
Understanding Expertise through Demonstrations: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning. CoRR abs/2302.07457 (2023) - [i99]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 abs/2303.02343 (2023) - [i98]Xinwei Zhang, Mingyi Hong, Jie Chen:
GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data. CoRR abs/2303.09531 (2023) - [i97]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 abs/2305.04241 (2023) - [i96]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 abs/2308.00788 (2023) - [i95]Ran Wei, Siliang Zeng, Chenliang Li, Alfredo García, Anthony D. McDonald
, Mingyi Hong:
A Bayesian Approach to Robust Inverse Reinforcement Learning. CoRR abs/2309.08571 (2023) - [i94]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 abs/2310.08782 (2023) - [i93]Ganghua Wang, Xun Xian, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding:
Demystifying Poisoning Backdoor Attacks from a Statistical Perspective. CoRR abs/2310.10780 (2023) - [i92]Xinwei Zhang, Zhiqi Bu, Zhiwei Steven Wu, Mingyi Hong:
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach. CoRR abs/2311.14632 (2023) - 2022
- [j73]Junyu Zhang
, Mingyi Hong, Shuzhong Zhang:
On lower iteration complexity bounds for the convex concave saddle point problems. Math. Program. 194(1): 901-935 (2022) - [j72]Mingyi Hong, Siliang Zeng, Junyu Zhang, Haoran Sun:
On the Divergence of Decentralized Nonconvex Optimization. SIAM J. Optim. 32(4): 2879-2908 (2022) - [j71]Sagar Shrestha, Xiao Fu
, Mingyi Hong
:
Deep Spectrum Cartography: Completing Radio Map Tensors Using Learned Neural Models. IEEE Trans. Signal Process. 70: 1170-1184 (2022) - [j70]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: 1803-1818 (2022) - [j69]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: 1900-1917 (2022) - [j68]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: 4277-4290 (2022) - [j67]Xinran Wang
, Jiawei Zhang
, Mingyi Hong
, Yuhong Yang
, Jie Ding
:
Parallel Assisted Learning. IEEE Trans. Signal Process. 70: 5848-5858 (2022) - [c115]Xun Xian, Mingyi Hong, Jie Ding:
Mismatched Supervised Learning. ICASSP 2022: 4228-4232 - [c114]Ioannis C. Tsaknakis, Prashant Khanduri, Mingyi Hong:
An Implicit Gradient-Type Method for Linearly Constrained Bilevel Problems. ICASSP 2022: 5438-5442 - [c113]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 - [c112]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 - [c111]Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Steven Wu, Jinfeng Yi:
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. ICML 2022: 26048-26067 - [c110]Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Nicola Elia:
A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms. ICML 2022: 26206-26222 - [c109]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: 26693-26712 - [c108]Siliang Zeng, Tianyi Chen, Alfredo García
, Mingyi Hong:
Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees. L4DC 2022: 278-290 - [c107]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 - [c106]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 - [c105]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 - [c104]Siliang Zeng, Chenliang Li, Alfredo García, Mingyi Hong:
Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees. NeurIPS 2022 - [c103]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 - [c102]Xun Xian, Mingyi Hong, Jie Ding:
Understanding Model Extraction Games. TPS-ISA 2022: 285-294 - [c101]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: 2353-2363 - [i91]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 abs/2203.14195 (2022) - [i90]Xinwei Zhang, Mingyi Hong, Nicola Elia:
Understanding A Class of Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective. CoRR abs/2204.12663 (2022) - [i89]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 abs/2206.02785 (2022) - [i88]Sagar Shrestha, Xiao Fu, Mingyi Hong:
Optimal Solutions for Joint Beamforming and Antenna Selection: From Branch and Bound to Machine Learning. CoRR abs/2206.05576 (2022) - [i87]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 abs/2206.06257 (2022) - [i86]Xun Xian, Mingyi Hong, Jie Ding:
A Framework for Understanding Model Extraction Attack and Defense. CoRR abs/2206.11480 (2022) - [i85]Siliang Zeng, Mingyi Hong, Alfredo García
:
Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees. CoRR abs/2210.01282 (2022) - [i84]Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao
, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu:
Advancing Model Pruning via Bi-level Optimization. CoRR abs/2210.04092 (2022) - [i83]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) - 2021
- [j66]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): 798-815 (2021) - [j65]Yijian Zhang, Emiliano Dall'Anese
, Mingyi Hong
:
Online Proximal-ADMM for Time-Varying Constrained Convex Optimization. IEEE Trans. Signal Inf. Process. over Networks 7: 144-155 (2021) - [j64]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: 4859-4874 (2021) - [j63]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: 6055-6070 (2021) - [j62]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): 10222-10235 (2021) - [c100]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: 895-899 - [c99]Junyu Zhang, Mingyi Hong, Mengdi Wang, Shuzhong Zhang:
Generalization Bounds for Stochastic Saddle Point Problems. AISTATS 2021: 568-576 - [c98]Ioannis C. Tsaknakis, Mingyi Hong:
Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda Function. AISTATS 2021: 1189-1197 - [c97]Wenqiang Pu, Shahana Ibrahim, Xiao Fu, Mingyi Hong:
Fiber-Sampled Stochastic Mirror Descent for Tensor Decomposition with β-Divergence. ICASSP 2021: 2925-2929 - [c96]Sagar Shrestha, Xiao Fu, Mingyi Hong:
Deep Generative Model Learning For Blind Spectrum Cartography with NMF-Based Radio Map Disaggregation. ICASSP 2021: 4920-4924 - [c95]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: 4945-4949 - [c94]Naichen Shi, Dawei Li, Mingyi Hong, Ruoyu Sun:
RMSprop converges with proper hyper-parameter. ICLR 2021 - [c93]Shixiang Chen, Alfredo García, Mingyi Hong, Shahin Shahrampour:
Decentralized Riemannian Gradient Descent on the Stiefel Manifold. ICML 2021: 1594-1605 - [c92]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: 6050-6061 - [c91]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 - [c90]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: 30271-30283 - [c89]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: 211-215 - [i82]Shixiang Chen, Alfredo García, Mingyi Hong, Shahin Shahrampour:
On the Local Linear Rate of Consensus on the Stiefel Manifold. CoRR abs/2101.09346 (2021) - [i81]Shixiang Chen, Alfredo García, Mingyi Hong, Shahin Shahrampour:
Decentralized Riemannian Gradient Descent on the Stiefel Manifold. CoRR abs/2102.07091 (2021) - [i80]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 abs/2102.07367 (2021) - [i79]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 abs/2102.13066 (2021) - [i78]Wenqiang Pu, Shahana Ibrahim, Xiao Fu, Mingyi Hong:
Stochastic Mirror Descent for Low-Rank Tensor Decomposition Under Non-Euclidean Losses. CoRR abs/2104.14562 (2021) - [i77]Sagar Shrestha, Xiao Fu, Mingyi Hong:
Deep Spectrum Cartography: Completing Radio Map Tensors Using Learned Neural Models. CoRR abs/2105.00177 (2021) - [i76]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. CoRR abs/2105.01696 (2021) - [i75]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. CoRR abs/2106.10435 (2021) - [i74]Xinwei Zhang, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Jinfeng Yi:
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy. CoRR abs/2106.13673 (2021) - [i73]Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Marco Nie, Zhaoran Wang:
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Finds Global Optima. CoRR abs/2110.01212 (2021) - [i72]Siliang Zeng, Tianyi Chen, Alfredo García, Mingyi Hong:
Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees. CoRR abs/2110.05597 (2021) - [i71]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 abs/2112.12376 (2021) - [i70]Bingqing Song, Haoran Sun, Wenqiang Pu, Sijia Liu, Mingyi Hong:
To Supervise or Not: How to Effectively Learn Wireless Interference Management Models? CoRR abs/2112.14011 (2021) - 2020
- [j61]Ying Cui, Tsung-Hui Chang
, Mingyi Hong, Jong-Shi Pang:
A Study of Piecewise Linear-Quadratic Programs. J. Optim. Theory Appl. 186(2): 523-553 (2020) - [j60]Seyed Amir Hossein Hosseini
, Burhaneddin Yaman
, Steen Moeller
, Mingyi Hong
, Mehmet Akçakaya
:
Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms. IEEE J. Sel. Top. Signal Process. 14(6): 1280-1291 (2020) - [j59]Mingyi Hong
, Tsung-Hui Chang
, Xiangfeng Wang, Meisam Razaviyayn, Shiqian Ma
, Zhi-Quan Luo:
A Block Successive Upper-Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization. Math. Oper. Res. 45(3): 833-861 (2020) - [j58]Tsung-Hui Chang
, Mingyi Hong
, Hoi-To Wai
, Xinwei Zhang, Songtao Lu
:
Distributed Learning in the Nonconvex World: From batch data to streaming and beyond. IEEE Signal Process. Mag. 37(3): 26-38 (2020) - [j57]Meisam Razaviyayn
, Tianjian Huang, Songtao Lu
, Maher Nouiehed, Maziar Sanjabi, Mingyi Hong
:
Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. IEEE Signal Process. Mag. 37(5): 55-66 (2020) - [j56]Guoyong Zhang
, Xiao Fu
, Jun Wang
, Xi-Le Zhao
, Mingyi Hong
:
Spectrum Cartography via Coupled Block-Term Tensor Decomposition. IEEE Trans. Signal Process. 68: 3660-3675 (2020) - [j55]Songtao Lu
, Ioannis C. Tsaknakis
, Mingyi Hong
, Yongxin Chen
:
Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications. IEEE Trans. Signal Process. 68: 3676-3691 (2020) - [j54]Qingjiang Shi
, Mingyi Hong
:
Penalty Dual Decomposition Method for Nonsmooth Nonconvex Optimization - Part I: Algorithms and Convergence Analysis. IEEE Trans. Signal Process. 68: 4108-4122 (2020) - [j53]Qingjiang Shi
, Mingyi Hong
, Xiao Fu
, Tsung-Hui Chang
:
Penalty Dual Decomposition Method for Nonsmooth Nonconvex Optimization - Part II: Applications. IEEE Trans. Signal Process. 68: 4242-4257 (2020) - [j52]Yi Wei
, Ming-Min Zhao
, Mingyi Hong
, Min-Jian Zhao, Ming Lei:
Learned Conjugate Gradient Descent Network for Massive MIMO Detection. IEEE Trans. Signal Process. 68: 6336-6349 (2020) - [c88]Xinwei Zhang, Victor Purba, Mingyi Hong, Sairaj V. Dhople:
A Sum-of-Squares Optimization Method for Learning and Controlling Photovoltaic Systems. ACC 2020: 2376-2381 - [c87]Ioannis C. Tsaknakis, Mingyi Hong, Sijia Liu:
Decentralized Min-Max Optimization: Formulations, Algorithms and Applications in Network Poisoning Attack. ICASSP 2020: 5755-5759 - [c86]Yi Wei, Ming-Min Zhao, Mingyi Hong, Min-Jian Zhao, Ming Lei:
Learned Conjugate Gradient Descent Network for Massive MIMO Detection. ICC 2020: 1-6 - [c85]Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O'Reilly:
Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks. ICML 2020: 6282-6293 - [c84]Haoran Sun, Songtao Lu, Mingyi Hong:
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking. ICML 2020: 9217-9228 - [c83]Xiangyi Chen, Tiancong Chen, Haoran Sun, Zhiwei Steven Wu
, Mingyi Hong:
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms. NeurIPS 2020 - [c82]Xiangyi Chen, Zhiwei Steven Wu
, Mingyi Hong:
Understanding Gradient Clipping in Private SGD: A Geometric Perspective. NeurIPS 2020 - [c81]Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong:
Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems. NeurIPS 2020 - [c80]Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong:
Provably Efficient Neural GTD for Off-Policy Learning. NeurIPS 2020 - [c79]Lingyun Zhou, Yihong Dong, Mingyi Hong, Qingjiang Shi:
Joint Channel Assignment And Power Allocation for Multi-UAVs Communication Systems. SPAWC 2020: 1-5 - [i69]Tsung-Hui Chang, Mingyi Hong, Hoi-To Wai, Xinwei Zhang, Songtao Lu:
Distributed Learning in the Non-Convex World: From Batch to Streaming Data, and Beyond. CoRR abs/2001.04786 (2020) - [i68]Yijian Zhang, Emiliano Dall'Anese
, Mingyi Hong:
Online Proximal-ADMM For Time-varying Constrained Optimization. CoRR abs/2005.03267 (2020) - [i67]Xinwei Zhang, Mingyi Hong, Sairaj V. Dhople, Wotao Yin, Yang Liu:
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data. CoRR abs/2005.11418 (2020) - [i66]Meisam Razaviyayn, Tianjian Huang, Songtao Lu, Maher Nouiehed, Maziar Sanjabi, Mingyi Hong:
Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. CoRR abs/2006.08141 (2020) - [i65]Mingyi Hong, Siliang Zeng, Junyu Zhang, Haoran Sun:
On the Divergence of Decentralized Non-Convex Optimization. CoRR abs/2006.11662 (2020) - [i64]Yingxue Zhou, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Arindam Banerjee:
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds. CoRR abs/2006.13501 (2020) - [i63]Xiangyi Chen, Zhiwei Steven Wu, Mingyi Hong:
Understanding Gradient Clipping in Private SGD: A Geometric Perspective. CoRR abs/2006.15429 (2020) - [i62]Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang:
A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic. CoRR abs/2007.05170 (2020) - [i61]Lingyun Zhou, Xihan Chen, Mingyi Hong, Shi Jin, Qingjiang Shi:
Joint Channel Assignment and Power Allocation for Multi-UAV Communication. CoRR abs/2008.08212 (2020) - [i60]Xun Xian, Xinran Wang, Mingyi Hong, Jie Ding, Reza Ghanadan:
Imitation Privacy. CoRR abs/2009.00442 (2020) - [i59]Minghe Zhu, Tsung-Hui Chang, Mingyi Hong:
Learning to Beamform in Heterogeneous Massive MIMO Networks. CoRR abs/2011.03971 (2020) - [i58]Haoran Sun, Wenqiang Pu, Minghe Zhu, Xiao Fu, Tsung-Hui Chang, Mingyi Hong:
Learning to Continuously Optimize Wireless Resource In Episodically Dynamic Environment. CoRR abs/2011.07782 (2020) - [i57]Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen:
Hybrid Federated Learning: Algorithms and Implementation. CoRR abs/2012.12420 (2020) - [i56]Han Shen, Kaiqing Zhang, Mingyi Hong, Tianyi Chen:
Asynchronous Advantage Actor Critic: Non-asymptotic Analysis and Linear Speedup. CoRR abs/2012.15511 (2020)
2010 – 2019
- 2019
- [j51]Davood Hajinezhad, Mingyi Hong
:
Perturbed proximal primal-dual algorithm for nonconvex nonsmooth optimization. Math. Program. 176(1-2): 207-245 (2019) - [j50]Meisam Razaviyayn, Mingyi Hong, Navid Reyhanian, Zhi-Quan Luo:
A linearly convergent doubly stochastic Gauss-Seidel algorithm for solving linear equations and a certain class of over-parameterized optimization problems. Math. Program. 176(1-2): 465-496 (2019) - [j49]Xiao Fu
, Kejun Huang
, Nicholas D. Sidiropoulos
, Qingjiang Shi
, Mingyi Hong
:
Anchor-Free Correlated Topic Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 41(5): 1056-1071 (2019) - [j48]Davood Hajinezhad
, Mingyi Hong
, Alfredo García
:
ZONE: Zeroth-Order Nonconvex Multiagent Optimization Over Networks. IEEE Trans. Autom. Control. 64(10): 3995-4010 (2019) - [j47]Charilaos I. Kanatsoulis
, Xiao Fu
, Nicholas D. Sidiropoulos
, Mingyi Hong
:
Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data. IEEE Trans. Signal Process. 67(2): 306-319 (2019) - [j46]Haoran Sun
, Mingyi Hong
:
Distributed Non-Convex First-Order Optimization and Information Processing: Lower Complexity Bounds and Rate Optimal Algorithms. IEEE Trans. Signal Process. 67(22): 5912-5928 (2019) - [c78]Xinwei Zhang, John Sartori, Mingyi Hong, Sairaj V. Dhople:
DImplementing First-order Optimization Methods: Algorithmic Considerations and Bespoke Microcontrollers. ACSSC 2019: 296-300 - [c77]Songtao Lu, Rahul Singh, Xiangyi Chen, Yongxin Chen, Mingyi Hong:
Alternating Gradient Descent Ascent for Nonconvex Min-Max Problems in Robust Learning and GANs. ACSSC 2019: 680-684 - [c76]Guoyong Zhang, Xiao Fu, Jun Wang, Mingyi Hong:
Coupled Block-term Tensor Decomposition Based Blind Spectrum Cartography. ACSSC 2019: 1644-1648 - [c75]Jennifer Annoni, Emiliano Dall'Anese, Mingyi Hong, Christopher J. Bay:
Efficient Distributed Optimization of Wind Farms Using Proximal Primal-Dual Algorithms. ACC 2019: 4173-4178 - [c74]Kejun Huang, Zhuoran Yang, Zhaoran Wang, Mingyi Hong:
Learning Partially Observable Markov Decision Processes Using Coupled Canonical Polyadic Decomposition. DSW 2019: 295-299 - [c73]Songtao Lu, Xinwei Zhang, Haoran Sun
, Mingyi Hong:
GNSD: a Gradient-Tracking Based Nonconvex Stochastic Algorithm for Decentralized Optimization. DSW 2019: 315-321 - [c72]Haoran Sun
, Aliye Özge Kaya, Mike Macdonald, Harish Viswanathan, Mingyi Hong:
Deep Learning Based Preamble Detection and TOA Estimation. GLOBECOM 2019: 1-6 - [c71]Songtao Lu, Mingyi Hong, Zhengdao Wang
:
Fast and Global Optimal Nonconvex Matrix Factorization via Perturbed Alternating Proximal Point. ICASSP 2019: 2907-2911 - [c70]Songtao Lu, Ioannis C. Tsaknakis, Mingyi Hong:
Block Alternating Optimization for Non-convex Min-max Problems: Algorithms and Applications in Signal Processing and Communications. ICASSP 2019: 4754-4758 - [c69]Songtao Lu, Ziping Zhao, Kejun Huang, Mingyi Hong:
Perturbed Projected Gradient Descent Converges to Approximate Second-order Points for Bound Constrained Nonconvex Problems. ICASSP 2019: 5356-5360 - [c68]Xiangyi Chen, Sijia Liu, Ruoyu Sun, Mingyi Hong:
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization. ICLR (Poster) 2019 - [c67]Sijia Liu, Pin-Yu Chen, Xiangyi Chen, Mingyi Hong:
signSGD via Zeroth-Order Oracle. ICLR (Poster) 2019 - [c66]Songtao Lu, Mingyi Hong, Zhengdao Wang:
PA-GD: On the Convergence of Perturbed Alternating Gradient Descent to Second-Order Stationary Points for Structured Nonconvex Optimization. ICML 2019: 4134-4143 - [c65]Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin:
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective. IJCAI 2019: 3961-3967 - [c64]Hoi-To Wai, Mingyi Hong, Zhuoran Yang, Zhaoran Wang, Kexin Tang:
Variance Reduced Policy Evaluation with Smooth Function Approximation. NeurIPS 2019: 5776-5787 - [c63]Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David D. Cox:
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization. NeurIPS 2019: 7202-7213 - [c62]Zhuoran Yang, Yongxin Chen, Mingyi Hong, Zhaoran Wang:
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost. NeurIPS 2019: 8351-8363 - [c61]Xingguo Li, Haoming Jiang, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao:
On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. UAI 2019: 49-59 - [c60]Kexin Tang, Nuowen Kan, Junni Zou, Xiao Fu, Mingyi Hong, Hongkai Xiong
:
Multiuser Video Streaming Rate Adaptation: A Physical Layer Resource-Aware Deep Reinforcement Learning Approach. VCIP 2019: 1-4 - [i55]Qi Cai, Mingyi Hong, Yongxin Chen, Zhaoran Wang:
On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator. CoRR abs/1901.03674 (2019) - [i54]Kexin Tang, Nuowen Kan, Junni Zou, Xiao Fu, Mingyi Hong, Hongkai Xiong:
Multiuser Video Streaming Rate Adaptation: A Physical Layer Resource-Aware Deep Reinforcement Learning Approach. CoRR abs/1902.00637 (2019) - [i53]Xiangyi Chen, Tiancong Chen, Haoran Sun, Zhiwei Steven Wu, Mingyi Hong:
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms. CoRR abs/1906.01736 (2019) - [i52]Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin:
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective. CoRR abs/1906.04214 (2019) - [i51]Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong:
SNAP: Finding Approximate Second-Order Stationary Solutions Efficiently for Non-convex Linearly Constrained Problems. CoRR abs/1907.04450 (2019) - [i50]Zhuoran Yang, Yongxin Chen, Mingyi Hong, Zhaoran Wang:
On the Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost. CoRR abs/1907.06246 (2019) - [i49]Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O'Reilly:
Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML. CoRR abs/1909.13806 (2019) - [i48]Haoran Sun
, Songtao Lu, Mingyi Hong:
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: A Joint Gradient Estimation and Tracking Approach. CoRR abs/1910.05857 (2019) - [i47]Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David D. Cox:
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization. CoRR abs/1910.06513 (2019) - [i46]Seyed Amir Hossein Hosseini, Burhaneddin Yaman, Steen Moeller, Mingyi Hong, Mehmet Akçakaya:
Dense Recurrent Neural Networks for Inverse Problems: History-Cognizant Unrolling of Optimization Algorithms. CoRR abs/1912.07197 (2019) - [i45]Yang Liu, Yan Kang, Xinwei Zhang, Liping Li, Yong Cheng, Tianjian Chen, Mingyi Hong, Qiang Yang:
A Communication Efficient Vertical Federated Learning Framework. CoRR abs/1912.11187 (2019) - 2018
- [j45]Qingjiang Shi
, Mingyi Hong
:
Spectral Efficiency Optimization For Millimeter Wave Multiuser MIMO Systems. IEEE J. Sel. Top. Signal Process. 12(3): 455-468 (2018) - [j44]Mingyi Hong
:
A Distributed, Asynchronous, and Incremental Algorithm for Nonconvex Optimization: An ADMM Approach. IEEE Trans. Control. Netw. Syst. 5(3): 935-945 (2018) - [j43]Yijian Zhang, Mingyi Hong
, Emiliano Dall'Anese
, Sairaj V. Dhople
, Zi Xu:
Distributed Controllers Seeking AC Optimal Power Flow Solutions Using ADMM. IEEE Trans. Smart Grid 9(5): 4525-4537 (2018) - [j42]Wei-Cheng Liao
, Mingyi Hong
, Hamid Farmanbar
, Zhi-Quan Luo:
A Distributed Semiasynchronous Algorithm for Network Traffic Engineering. IEEE Trans. Signal Inf. Process. over Networks 4(3): 436-450 (2018) - [j41]Haoran Sun
, Xiangyi Chen, Qingjiang Shi
, Mingyi Hong
, Xiao Fu
, Nicholas D. Sidiropoulos
:
Learning to Optimize: Training Deep Neural Networks for Interference Management. IEEE Trans. Signal Process. 66(20): 5438-5453 (2018) - [c59]Haoran Sun
, Mingyi Hong:
Distributed Non-Convex First-Order optimization and Information Processing: Lower Complexity Bounds and Rate Optimal Algorithms. ACSSC 2018: 38-42 - [c58]Ziping Zhao, Songtao Lu, Mingyi Hong, Daniel P. Palomar
:
Distributed optimization for Generalized Phase Retrieval Over Networks. ACSSC 2018: 48-52 - [c57]Zhuoran Yang, Kaiqing Zhang, Mingyi Hong, Tamer Basar:
A Finite Sample Analysis of the Actor-Critic Algorithm. CDC 2018: 2759-2764 - [c56]Nan Zhang, Ya-Feng Liu, Hamid Farmanbar, Tsung-Hui Chang
, Mingyi Hong, Zhi-Quan Luo:
Software Defined Resource Allocation for Service-Oriented Networks. ICASSP 2018: 3769-3773 - [c55]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos
, Mingyi Hong:
Large-Scale Regularized Sumcor GCCA via Penalty-Dual Decomposition. ICASSP 2018: 6363-6367 - [c54]Mingyi Hong, Meisam Razaviyayn, Jason D. Lee:
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks. ICML 2018: 2014-2023 - [c53]Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong:
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization. NeurIPS 2018: 9672-9683 - [c52]Mohamed Salah Ibrahim
, Aritra Konar, Mingyi Hong, Nicholas D. Sidiropoulos
:
Mirror-Prox SCA Algorithm for Multicast Beamforming and Antenna Selection. SPAWC 2018: 1-5 - [c51]Haoran Sun
, Ziping Zhao
, Xiao Fu, Mingyi Hong:
Limited Feedback Double Directional Massive MIMO Channel Estimation: From Low-Rank Modeling to Deep Learning. SPAWC 2018: 1-5 - [i44]Qingjiang Shi, Mingyi Hong:
Spectral Efficiency Optimization For Millimeter Wave Multi-User MIMO Systems. CoRR abs/1801.07560 (2018) - [i43]Mingyi Hong, Jason D. Lee, Meisam Razaviyayn:
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solutions for Nonconvex Distributed Optimization. CoRR abs/1802.08941 (2018) - [i42]Songtao Lu, Mingyi Hong, Zhengdao Wang:
On the Sublinear Convergence of Randomly Perturbed Alternating Gradient Descent to Second Order Stationary Solutions. CoRR abs/1802.10418 (2018) - [i41]Mohamed Salah Ibrahim, Aritra Konar, Mingyi Hong, Nicholas D. Sidiropoulos:
Mirror-Prox SCA Algorithm for Multicast Beamforming and Antenna Selection. CoRR abs/1803.00678 (2018) - [i40]Haoran Sun, Mingyi Hong:
Distributed Non-Convex First-Order Optimization and Information Processing: Lower Complexity Bounds and Rate Optimal Algorithms. CoRR abs/1804.02729 (2018) - [i39]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong:
Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data. CoRR abs/1804.08806 (2018) - [i38]Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong:
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization. CoRR abs/1806.00877 (2018) - [i37]Xiangyi Chen, Sijia Liu, Ruoyu Sun, Mingyi Hong:
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization. CoRR abs/1808.02941 (2018) - 2017
- [j40]Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong:
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. J. Mach. Learn. Res. 18: 184:1-184:24 (2017) - [j39]Nan Zhang, Ya-Feng Liu
, Hamid Farmanbar, Tsung-Hui Chang
, Mingyi Hong
, Zhi-Quan Luo:
Network Slicing for Service-Oriented Networks Under Resource Constraints. IEEE J. Sel. Areas Commun. 35(11): 2512-2521 (2017) - [j38]Mingyi Hong, Zhi-Quan Luo:
On the linear convergence of the alternating direction method of multipliers. Math. Program. 162(1-2): 165-199 (2017) - [j37]Mingyi Hong, Xiangfeng Wang, Meisam Razaviyayn, Zhi-Quan Luo:
Iteration complexity analysis of block coordinate descent methods. Math. Program. 163(1-2): 85-114 (2017) - [j36]Ming-Min Zhao, Yunlong Cai
, Qingjiang Shi, Mingyi Hong, Benoît Champagne:
Joint Transceiver Designs for Full-Duplex $K$ -Pair MIMO Interference Channel With SWIPT. IEEE Trans. Commun. 65(2): 890-905 (2017) - [j35]Mingyi Hong, Tsung-Hui Chang
:
Stochastic Proximal Gradient Consensus Over Random Networks. IEEE Trans. Signal Process. 65(11): 2933-2948 (2017) - [j34]Songtao Lu
, Mingyi Hong, Zhengdao Wang
:
A Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization: Convergence Analysis and Optimality. IEEE Trans. Signal Process. 65(12): 3120-3135 (2017) - [j33]Xiao Fu, Kejun Huang, Mingyi Hong, Nicholas D. Sidiropoulos
, Anthony Man-Cho So
:
Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis. IEEE Trans. Signal Process. 65(16): 4150-4165 (2017) - [c50]Songtao Lu, Mingyi Hong, Zhengdao Wang:
A Stochastic Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization. AISTATS 2017: 812-821 - [c49]Yijian Zhang, Emiliano Dall'Anese
, Mingyi Hong, Sairaj V. Dhople, Zi Xu:
Regulation of renewable energy sources to optimal power flow solutions using ADMM. ACC 2017: 3394-3399 - [c48]Yijian Zhang, Emiliano Dall'Anese
, Mingyi Hong:
Dynamic ADMM for real-time optimal power flow. GlobalSIP 2017: 1085-1089 - [c47]Xiongfei Zhai, Qingjiang Shi, Yunlong Cai, Mingyi Hong, Minjian Zhao:
Hybrid Transceiver Design for mmWave MIMO Systems with Non-Linear Power Consumption Model. GLOBECOM 2017: 1-6 - [c46]Songtao Lu, Mingyi Hong, Zhengdao Wang:
A nonconvex splitting method for symmetric nonnegative matrix factorization: Convergence analysis and optimality. ICASSP 2017: 2572-2576 - [c45]Nan Zhang, Wei-Cheng Liao, Mingyi Hong, Hamid Farmanbar, Zhi-Quan Luo:
Traffic engineering for backhaul networks with wireless link scheduling. ICASSP 2017: 3719-3723 - [c44]Qingjiang Shi, Mingyi Hong:
Penalty dual decomposition method with application in signal processing. ICASSP 2017: 4059-4063 - [c43]Xiao Fu, Kejun Huang, Mingyi Hong, Nicholas D. Sidiropoulos
, Anthony Man-Cho So
:
Scalable and flexible Max-Var generalized canonical correlation analysis via alternating optimization. ICASSP 2017: 5855-5859 - [c42]Mingyi Hong, Davood Hajinezhad, Ming-Min Zhao:
Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning Over Networks. ICML 2017: 1529-1538 - [c41]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos
, Mingyi Hong:
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering. ICML 2017: 3861-3870 - [c40]Haoran Sun
, Xiangyi Chen, Qingjiang Shi, Mingyi Hong, Xiao Fu, Nikos D. Sidiropoulos
:
Learning to optimize: Training deep neural networks for wireless resource management. SPAWC 2017: 1-6 - [c39]Ming-Min Zhao, Qingjiang Shi, Mingyi Hong, Yunlong Cai, Minjian Zhao:
Joint Transceiver Design for Full-Duplex Cloud Radio Access Networks with SWIPT. WCNC 2017: 1-6 - [i36]Haoran Sun, Xiangyi Chen, Qingjiang Shi, Mingyi Hong, Xiao Fu, Nikos D. Sidiropoulos:
Learning to Optimize: Training Deep Neural Networks for Wireless Resource Management. CoRR abs/1705.09412 (2017) - [i35]Nan Zhang, Ya-Feng Liu, Hamid Farmanbar, Tsung-Hui Chang, Mingyi Hong, Zhi-Quan Luo:
Network Slicing for Service-Oriented Networks Under Resource Constraints. CoRR abs/1708.07463 (2017) - [i34]Qingjiang Shi, Mingyi Hong, Xiao Fu, Tsung-Hui Chang:
Penalty Dual Decomposition Method For Nonsmooth Nonconvex Optimization. CoRR abs/1712.04767 (2017) - 2016
- [j32]Brendan P. W. Ames
, Mingyi Hong:
Alternating direction method of multipliers for penalized zero-variance discriminant analysis. Comput. Optim. Appl. 64(3): 725-754 (2016) - [j31]Mingyi Hong, Zhi-Quan Luo, Meisam Razaviyayn:
Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems. SIAM J. Optim. 26(1): 337-364 (2016) - [j30]Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo, Jong-Shi Pang:
A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data: With applications in machine learning and signal processing. IEEE Signal Process. Mag. 33(1): 57-77 (2016) - [j29]Alfredo García
, Mingyi Hong:
Efficient Rate Allocation in Wireless Networks Under Incomplete Information. IEEE Trans. Autom. Control. 61(5): 1397-1402 (2016) - [j28]Qingjiang Shi, Cheng Peng, WeiQiang Xu, Mingyi Hong, Yunlong Cai:
Energy Efficiency Optimization for MISO SWIPT Systems With Zero-Forcing Beamforming. IEEE Trans. Signal Process. 64(4): 842-854 (2016) - [j27]Qingjiang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo:
SINR Constrained Beamforming for a MIMO Multi-User Downlink System: Algorithms and Convergence Analysis. IEEE Trans. Signal Process. 64(11): 2920-2933 (2016) - [j26]Tsung-Hui Chang
, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang:
Asynchronous Distributed ADMM for Large-Scale Optimization - Part I: Algorithm and Convergence Analysis. IEEE Trans. Signal Process. 64(12): 3118-3130 (2016) - [j25]Tsung-Hui Chang
, Wei-Cheng Liao, Mingyi Hong, Xiangfeng Wang:
Asynchronous Distributed ADMM for Large-Scale Optimization - Part II: Linear Convergence Analysis and Numerical Performance. IEEE Trans. Signal Process. 64(12): 3131-3144 (2016) - [j24]Qingjiang Shi, Mingyi Hong, Xiqi Gao
, Enbin Song, Yunlong Cai, WeiQiang Xu:
Joint Source-Relay Design for Full-Duplex MIMO AF Relay Systems. IEEE Trans. Signal Process. 64(23): 6118-6131 (2016) - [j23]Mingyi Hong, Qiang Li, Ya-Feng Liu:
Decomposition by Successive Convex Approximation: A Unifying Approach for Linear Transceiver Design in Heterogeneous Networks. IEEE Trans. Wirel. Commun. 15(2): 1377-1392 (2016) - [j22]Ya-Feng Liu, Mingyi Hong, Enbin Song:
Sample Approximation-Based Deflation Approaches for Chance SINR-Constrained Joint Power and Admission Control. IEEE Trans. Wirel. Commun. 15(7): 4535-4547 (2016) - [c38]Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong:
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. AISTATS 2016: 491-499 - [c37]Ming-Min Zhao, Qingjiang Shi, Mingyi Hong:
A distributed algorithm for dictionary learning over networks. GlobalSIP 2016: 505-509 - [c36]Qingjiang Shi, Mingyi Hong, Enbin Song, Yunlong Cai, WeiQiang Xu:
A penalty-BSUM approach for rate optimization in full-duplex MIMO relay networks with relay processing delay. ICASSP 2016: 3646-3650 - [c35]Shengyu Zhu, Mingyi Hong, Biao Chen:
Quantized consensus ADMM for multi-agent distributed optimization. ICASSP 2016: 4134-4138 - [c34]Davood Hajinezhad, Tsung-Hui Chang
, Xiangfeng Wang, Qingjiang Shi, Mingyi Hong:
Nonnegative matrix factorization using ADMM: Algorithm and convergence analysis. ICASSP 2016: 4742-4746 - [c33]Mingyi Hong, Tsung-Hui Chang
:
Stochastic proximal gradient consensus over time-varying networks. ICASSP 2016: 4776-4780 - [c32]Tsung-Hui Chang
, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang:
Asynchronous distributed alternating direction method of multipliers: Algorithm and convergence analysis. ICASSP 2016: 4781-4785 - [c31]Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang:
NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization. NIPS 2016: 3207-3215 - [c30]Yunlong Cai, Ming-Min Zhao, Qingjiang Shi, Mingyi Hong, Benoît Champagne:
Joint Transceiver Design for Full-Duplex K-Pair MIMO Interference Channel with Energy Harvesting. VTC Fall 2016: 1-5 - [p1]Mingyi Hong, Wei-Cheng Liao, Ruoyu Sun, Zhi-Quan Luo:
Optimization algorithms for big data with application in wireless networks. Big Data over Networks 2016: 66-100 - [i33]Mingyi Hong:
Decomposing Linearly Constrained Nonconvex Problems by a Proximal Primal Dual Approach: Algorithms, Convergence, and Applications. CoRR abs/1604.00543 (2016) - [i32]Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang:
NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization. CoRR abs/1605.07747 (2016) - [i31]Xingguo Li, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao:
A First Order Free Lunch for SQRT-Lasso. CoRR abs/1605.07950 (2016) - [i30]Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong:
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. CoRR abs/1607.02793 (2016) - [i29]Qingjiang Shi, Haoran Sun, Songtao Lu, Mingyi Hong, Meisam Razaviyayn:
Inexact Block Coordinate Descent Methods For Symmetric Nonnegative Matrix Factorization. CoRR abs/1607.03092 (2016) - [i28]Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, WeiQiang Xu:
Joint Source-Relay Design for Full-Duplex MIMO AF Relay Systems. CoRR abs/1607.03128 (2016) - [i27]Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong:
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering. CoRR abs/1610.04794 (2016) - 2015
- [j21]Ruoyu Sun, Mingyi Hong, Zhi-Quan Luo:
Joint Downlink Base Station Association and Power Control for Max-Min Fairness: Computation and Complexity. IEEE J. Sel. Areas Commun. 33(6): 1040-1054 (2015) - [j20]Tsung-Hui Chang
, Mingyi Hong, Xiangfeng Wang:
Multi-Agent Distributed Optimization via Inexact Consensus ADMM. IEEE Trans. Signal Process. 63(2): 482-497 (2015) - [c29]Cheng Peng, Qingjiang Shi, WeiQiang Xu, Mingyi Hong:
Energy efficiency optimization for multi-user MISO swipt systems. ChinaSIP 2015: 772-776 - [c28]Davood Hajinezhad, Mingyi Hong:
Nonconvex alternating direction method of multipliers for distributed sparse principal component analysis. GlobalSIP 2015: 255-259 - [c27]Hung-Wei Tseng, Mingyi Hong, Zhi-Quan Luo:
Combining sparse NMF with deep neural network: A new classification-based approach for speech enhancement. ICASSP 2015: 2145-2149 - [c26]Wei-Cheng Liao, Mingyi Hong, Hamid Farmanbar, Zhi-Quan Luo:
Semi-asynchronous routing for large scale hierarchical networks. ICASSP 2015: 2894-2898 - [c25]Mingyi Hong, Zhi-Quan Luo, Meisam Razaviyayn:
Convergence analysis of alternating direction method of multipliers for a family of nonconvex problems. ICASSP 2015: 3836-3840 - [c24]Wei-Cheng Liao, Mingyi Hong, Ivo Merks, Tao Zhang, Zhi-Quan Luo:
Incorporating spatial information in binaural beamforming for noise suppression in hearing aids. ICASSP 2015: 5733-5737 - [c23]Ruoyu Sun, Mingyi Hong:
Improved Iteration Complexity Bounds of Cyclic Block Coordinate Descent for Convex Problems. NIPS 2015: 1306-1314 - [i26]Qingjiang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo:
SINR Constrained Beamforming for a MIMO Multi-user Downlink System. CoRR abs/1507.07115 (2015) - [i25]Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang:
Asynchronous Distributed ADMM for Large-Scale Optimization- Part I: Algorithm and Convergence Analysis. CoRR abs/1509.02597 (2015) - [i24]Tsung-Hui Chang, Wei-Cheng Liao, Mingyi Hong, Xiangfeng Wang:
Asynchronous Distributed ADMM for Large-Scale Optimization- Part II: Linear Convergence Analysis and Numerical Performance. CoRR abs/1509.02604 (2015) - [i23]Mingyi Hong, Tsung-Hui Chang:
Stochastic Proximal Gradient Consensus Over Random Networks. CoRR abs/1511.08905 (2015) - 2014
- [j19]Wei-Cheng Liao, Mingyi Hong, Hamid Farmanbar, Xu Li, Zhi-Quan Luo, Hang Zhang:
Min Flow Rate Maximization for Software Defined Radio Access Networks. IEEE J. Sel. Areas Commun. 32(6): 1282-1294 (2014) - [j18]Zi Xu
, Mingyi Hong, Zhi-Quan Luo:
Semidefinite Approximation for Mixed Binary Quadratically Constrained Quadratic Programs. SIAM J. Optim. 24(3): 1265-1293 (2014) - [j17]Hadi Baligh, Mingyi Hong, Wei-Cheng Liao, Zhi-Quan Luo, Meisam Razaviyayn, Maziar Sanjabi, Ruoyu Sun:
Cross-Layer Provision of Future Cellular Networks: A WMMSE-based approach. IEEE Signal Process. Mag. 31(6): 56-68 (2014) - [j16]José Joaquín Escudero Garzás, Mingyi Hong, Alfredo García
, Ana García Armada
:
Interference Pricing Mechanism for Downlink Multicell Coordinated Beamforming. IEEE Trans. Commun. 62(6): 1871-1883 (2014) - [j15]Wei-Cheng Liao, Mingyi Hong, Ya-Feng Liu, Zhi-Quan Luo:
Base Station Activation and Linear Transceiver Design for Optimal Resource Management in Heterogeneous Networks. IEEE Trans. Signal Process. 62(15): 3939-3952 (2014) - [j14]Shuai Ma, Mingyi Hong, Enbin Song, Xiangfeng Wang, Dechun Sun:
Outage Constrained Robust Secure Transmission for MISO Wiretap Channels. IEEE Trans. Wirel. Commun. 13(10): 5558-5570 (2014) - [c22]Wei-Cheng Liao, Mingyi Hong, Zhi-Quan Luo:
Max-min network flow and resource allocation for backhaul constrained heterogeneous wireless networks. ICASSP 2014: 845-849 - [c21]Tsung-Hui Chang
, Mingyi Hong, Xiangfeng Wang:
Multi-agent distributed large-scale optimization by inexact consensus alternating direction method of multipliers. ICASSP 2014: 6137-6141 - [c20]Mingyi Hong, Tsung-Hui Chang
, Xiangfeng Wang, Meisam Razaviyayn, Shiqian Ma, Zhi-Quan Luo:
A block coordinate descent method of multipliers: Convergence analysis and applications. ICASSP 2014: 7689-7693 - [c19]Xiangfeng Wang, Mingyi Hong, Tsung-Hui Chang
, Meisam Razaviyayn, Zhi-Quan Luo:
Joint day-ahead power procurement and load scheduling using stochastic alternating direction method of multipliers. ICASSP 2014: 7754-7758 - [c18]Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo, Jong-Shi Pang:
Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization. NIPS 2014: 1440-1448 - [c17]Mingyi Hong, Hao Zhu:
Power-efficient operation of wireless heterogeneous networks using Smart Grids. SmartGridComm 2014: 236-241 - [c16]Maziar Sanjabi, Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo:
Joint base station clustering and beamformer design for partial coordinated transmission using statistical channel state information. SPAWC 2014: 359-363 - [i22]Tsung-Hui Chang, Mingyi Hong, Xiangfeng Wang:
Multi-Agent Distributed Optimization via Inexact Consensus ADMM. CoRR abs/1402.6065 (2014) - [i21]Hadi Baligh, Mingyi Hong, Wei-Cheng Liao, Zhi-Quan Luo, Meisam Razaviyayn, Maziar Sanjabi, Ruoyu Sun:
Cross Layer Provision of Future Cellular Networks. CoRR abs/1407.1424 (2014) - [i20]Ruoyu Sun, Mingyi Hong, Zhi-Quan Luo:
Joint Downlink Base Station Association and Power Control for Max-Min Fairness: Computation and Complexity. CoRR abs/1407.2791 (2014) - [i19]Mingyi Hong:
A Distributed, Asynchronous and Incremental Algorithm for Nonconvex Optimization: An ADMM Based Approach. CoRR abs/1412.6058 (2014) - 2013
- [j13]Mingyi Hong, Ruoyu Sun, Hadi Baligh, Zhi-Quan Luo:
Joint Base Station Clustering and Beamformer Design for Partial Coordinated Transmission in Heterogeneous Networks. IEEE J. Sel. Areas Commun. 31(2): 226-240 (2013) - [j12]Qiang Li, Mingyi Hong, Hoi-To Wai, Ya-Feng Liu, Wing-Kin Ma
, Zhi-Quan Luo:
Transmit Solutions for MIMO Wiretap Channels using Alternating Optimization. IEEE J. Sel. Areas Commun. 31(9): 1714-1727 (2013) - [j11]Mingyi Hong, Zi Xu
, Meisam Razaviyayn, Zhi-Quan Luo:
Joint User Grouping and Linear Virtual Beamforming: Complexity, Algorithms and Approximation Bounds. IEEE J. Sel. Areas Commun. 31(10): 2013-2027 (2013) - [j10]Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo:
A Unified Convergence Analysis of Block Successive Minimization Methods for Nonsmooth Optimization. SIAM J. Optim. 23(2): 1126-1153 (2013) - [j9]Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo:
Linear transceiver design for a MIMO interfering broadcast channel achieving max-min fairness. Signal Process. 93(12): 3327-3340 (2013) - [j8]Ya-Feng Liu, Mingyi Hong, Yu-Hong Dai:
Max-Min Fairness Linear Transceiver Design Problem for a Multi-User SIMO Interference Channel is Polynomial Time Solvable. IEEE Signal Process. Lett. 20(1): 27-30 (2013) - [j7]Mingyi Hong, Zhi-Quan Luo:
Distributed Linear Precoder Optimization and Base Station Selection for an Uplink Heterogeneous Network. IEEE Trans. Signal Process. 61(12): 3214-3228 (2013) - [j6]Mingyi Hong, Alfredo García
, Jorge Barrera
, Stephen G. Wilson:
Joint Access Point Selection and Power Allocation for Uplink Wireless Networks. IEEE Trans. Signal Process. 61(13): 3334-3347 (2013) - [c15]Jorge Barrera
, Alfredo García
, Mingyi Hong:
Auction design for spectrum allocation under interference constraints. GLOBECOM 2013: 3035-3041 - [c14]Shu-Hsien Chu, Mingyi Hong, Zhi-Quan Luo, Kelly Fitz, Martin F. McKinney, Tao Zhang:
Derivative-free optimization of hearing aid parameters. ICASSP 2013: 393-397 - [c13]Qiang Li, Mingyi Hong, Hoi-To Wai, Wing-Kin Ma, Ya-Feng Liu, Zhi-Quan Luo:
An alternating optimization algorithm for the MIMO secrecy capacity problem under sum power and per-antenna power constraints. ICASSP 2013: 4359-4363 - [c12]Wei-Cheng Liao, Mingyi Hong, Zhi-Quan Luo:
Base station activation and linear transceiver design for utility maximization in Heterogeneous networks. ICASSP 2013: 4419-4423 - [c11]Hung-Wei Tseng, Srikanth Vishnubhotla, Mingyi Hong, Jinjun Xiao, Zhi-Quan Luo, Tao Zhang:
A novel single channel speech enhancement approach by combining Wiener filter and dictionary learning. ICASSP 2013: 8653-8657 - [c10]Hung-Wei Tseng, Srikanth Vishnubhotla, Mingyi Hong, Xiangfeng Wang, Jinjun Xiao, Zhi-Quan Luo, Tao Zhang:
A single channel speech enhancement approach by combining statistical criterion and multi-frame sparse dictionary learning. INTERSPEECH 2013: 451-455 - [i18]Xiangfeng Wang, Mingyi Hong, Shiqian Ma, Zhi-Quan Luo:
Solving Multiple-Block Separable Convex Minimization Problems Using Two-Block Alternating Direction Method of Multipliers. CoRR abs/1308.5294 (2013) - [i17]Wei-Cheng Liao, Mingyi Hong, Ya-Feng Liu, Zhi-Quan Luo:
Base Station Activation and Linear Transceiver Design for Optimal Resource Management in Heterogeneous Networks. CoRR abs/1309.4138 (2013) - [i16]Shuai Ma, Mingyi Hong, Enbin Song, Xiangfeng Wang, Dechun Sun:
Outage Constrained Robust Secure Transmission for MISO Wiretap Channels. CoRR abs/1310.7158 (2013) - [i15]Wei-Cheng Liao, Mingyi Hong, Hamid Farmanbar, Xu Li, Zhi-Quan Luo, Hang Zhang:
Min Flow Rate Maximization for Software Defined Radio Access Networks. CoRR abs/1312.5345 (2013) - 2012
- [j5]Alfredo García
, Mingyi Hong, Jorge Barrera
:
"Cap and Trade" for Congestion Control. Dyn. Games Appl. 2(3): 280-293 (2012) - [j4]Mingyi Hong, Alfredo García
:
Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network. IEEE J. Sel. Areas Commun. 30(11): 2238-2250 (2012) - [c9]Mingyi Hong, Meisam Razaviyayn, Ruoyu Sun, Zhi-Quan Luo:
Joint transceiver design and base station clustering for heterogeneous networks. ACSCC 2012: 574-578 - [c8]Qingjiang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo:
SINR constrained beamforming for a MIMO multi-user downlink system. ACSCC 2012: 1991-1995 - [c7]Mingyi Hong, Zhi-Quan Luo:
Joint linear precoder optimization and base station selection for an uplink MIMO network: A game theoretic approach. ICASSP 2012: 2941-2944 - [c6]Ruoyu Sun, Mingyi Hong, Zhi-Quan Luo:
Optimal joint base station assignment and power allocation in a cellular network. SPAWC 2012: 234-238 - [i14]Mingyi Hong, Ruoyu Sun, Hadi Baligh, Zhi-Quan Luo:
Joint Base Station Clustering and Beamformer Design for Partial Coordinated Transmission in Heterogenous Networks. CoRR abs/1203.6390 (2012) - [i13]Mingyi Hong, Alfredo García:
Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network. CoRR abs/1204.6105 (2012) - [i12]Mingyi Hong, Zhi-Quan Luo:
Distributed Linear Precoder Optimization and Base Station Selection for an Uplink Heterogeneous Network. CoRR abs/1205.0181 (2012) - [i11]Mingyi Hong, Zhi-Quan Luo:
Signal Processing and Optimal Resource Allocation for the Interference Channel. CoRR abs/1206.5144 (2012) - [i10]Mingyi Hong, Alfredo García, Jorge Barrera, Stephen G. Wilson:
Joint Access Point Selection and Power Allocation for Uplink Wireless Networks. CoRR abs/1207.4393 (2012) - [i9]Chenyang Li, Mingyi Hong, Randy Cogill, Alfredo García:
An Adaptive Online Ad Auction Scoring Algorithm for Revenue Maximization. CoRR abs/1207.4701 (2012) - [i8]Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo:
Linear Transceiver Design for a MIMO Interfering Broadcast Channel Achieving Max-Min Fairness. CoRR abs/1208.6357 (2012) - [i7]Mingyi Hong, Zi Xu, Meisam Razaviyayn, Zhi-Quan Luo:
Joint User Grouping and Linear Virtual Beamforming: Complexity, Algorithms and Approximation Bounds. CoRR abs/1209.4683 (2012) - [i6]Mingyi Hong, Qiang Li, Ya-Feng Liu, Zhi-Quan Luo:
Decomposition by Successive Convex Approximation: A Unifying Approach for Linear Transceiver Design in Heterogeneous Networks. CoRR abs/1210.1507 (2012) - 2011
- [j3]Mingyi Hong, Alfredo García
:
Averaged Iterative Water-Filling Algorithm: Robustness and Convergence. IEEE Trans. Signal Process. 59(5): 2448-2454 (2011) - [j2]Mingyi Hong, Alfredo García
:
Equilibrium Pricing of Interference in Cognitive Radio Networks. IEEE Trans. Signal Process. 59(12): 6058-6072 (2011) - [c5]Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo:
Linear transceiver design for a MIMO interfering broadcast channel achieving max-min fairness. ACSCC 2011: 1309-1313 - [c4]Mingyi Hong, Alfredo García
, Jorge Barrera
:
Joint distributed access point selection and power allocation in cognitive radio networks. INFOCOM 2011: 2516-2524 - [c3]Zhiheng Xie, Mingyi Hong, Hengchang Liu, Jingyuan Li, Kangyuan Zhu, John A. Stankovic:
Quantitative uncertainty-based incremental localization and anchor selection in wireless sensor networks. MSWiM 2011: 417-426 - [i5]Mingyi Hong, Alfredo García, Stephen G. Wilson:
Distributed Uplink Resource Allocation in Cognitive Radio Networks -- Part I: Equilibria and Algorithms for Power Allocation. CoRR abs/1102.1959 (2011) - [i4]Mingyi Hong, Alfredo García:
Averaged Iterative Water-Filling Algorithm: Robustness and Convergence. CoRR abs/1102.1960 (2011) - [i3]Mingyi Hong, Alfredo García, Jorge Barrera:
Distributed Uplink Resource Allocation in Cognitive Radio Networks -- Part II: Equilibria and Algorithms for Joint Access Point Selection and Power Allocation. CoRR abs/1102.1965 (2011) - [i2]Mingyi Hong, Alfredo García, Jorge Barrera:
Joint Distributed Access Point Selection and Power Allocation in Cognitive Radio Networks. CoRR abs/1102.2176 (2011) - [i1]Mingyi Hong, Alfredo García, José Joaquín Escudero Garzás, Ana García Armada:
Lower Bounds Optimization for Coordinated Linear Transmission Beamformer Design in Multicell Network Downlink. CoRR abs/1111.6223 (2011) - 2010
- [j1]Mingyi Hong, Mónica F. Bugallo
, Petar M. Djuric
:
Joint Model Selection and Parameter Estimation by Population Monte Carlo Simulation. IEEE J. Sel. Top. Signal Process. 4(3): 526-539 (2010) - [c2]Mingyi Hong, Alfredo García:
Competitive sharing of the spectrum in cognitive radio network: A market equilibrium framework. WiOpt 2010: 40-49
2000 – 2009
- 2009
- [c1]Mónica F. Bugallo
, Mingyi Hong, Petar M. Djuric
:
Marginalized population Monte Carlo. ICASSP 2009: 2925-2928
Coauthor Index
aka: Nikos D. Sidiropoulos
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