Mingyi Hong
Mingyi Hong
Associate Professor, University of Minnesota
Verified email at umn.edu - Homepage
Title
Cited by
Cited by
Year
A unified convergence analysis of block successive minimization methods for nonsmooth optimization
M Razaviyayn, M Hong, ZQ Luo
SIAM Journal on Optimization 23 (2), 1126-1153, 2013
8212013
On the linear convergence of the alternating direction method of multipliers.
M Hong, ZQ Luo
Mathematical Programming 162, 2017
6672017
Convergence analysis of alternating direction method of multipliers for a family of nonconvex problems
M Hong, ZQ Luo, M Razaviyayn
SIAM Journal on Optimization 26 (1), 337-364, 2016
6152016
Learning to optimize: Training deep neural networks for interference management
H Sun, X Chen, Q Shi, M Hong, X Fu, ND Sidiropoulos
IEEE Transactions on Signal Processing 66 (20), 5438-5453, 2018
464*2018
Towards k-means-friendly spaces: Simultaneous deep learning and clustering
B Yang, X Fu, ND Sidiropoulos, M Hong
international conference on machine learning, 3861-3870, 2017
4232017
Multi-agent distributed optimization via inexact consensus ADMM
TH Chang, M Hong, X Wang
IEEE Transactions on Signal Processing 63 (2), 482-497, 2014
3032014
Joint base station clustering and beamformer design for partial coordinated transmission in heterogeneous networks
M Hong, R Sun, H Baligh, ZQ Luo
IEEE Journal on Selected Areas in Communications 31 (2), 226-240, 2013
2972013
A unified algorithmic framework for block-structured optimization involving big data: With applications in machine learning and signal processing
M Hong, M Razaviyayn, ZQ Luo, JS Pang
IEEE Signal Processing Magazine 33 (1), 57-77, 2015
2712015
Transmit solutions for MIMO wiretap channels using alternating optimization
Q Li, M Hong, HT Wai, YF Liu, WK Ma, ZQ Luo
IEEE Journal on Selected Areas in Communications 31 (9), 1714-1727, 2013
1742013
On the convergence of a class of adam-type algorithms for non-convex optimization
X Chen, S Liu, R Sun, M Hong
International Conference on Learning Representations, 2018
1482018
Asynchronous distributed ADMM for large-scale optimization—Part I: Algorithm and convergence analysis
TH Chang, M Hong, WC Liao, X Wang
IEEE Transactions on Signal Processing 64 (12), 3118-3130, 2016
1412016
Asynchronous distributed ADMM for large-scale optimization—Part I: Algorithm and convergence analysis
TH Chang, M Hong, WC Liao, X Wang
IEEE Transactions on Signal Processing 64 (12), 3118-3130, 2016
1412016
Iteration complexity analysis of block coordinate descent methods
M Hong, X Wang, M Razaviyayn, ZQ Luo
Mathematical Programming 163 (1-2), 85-114, 2017
1332017
Energy efficiency optimization for MISO SWIPT systems with zero-forcing beamforming
Q Shi, C Peng, W Xu, M Hong, Y Cai
IEEE Transactions on Signal Processing 64 (4), 842-854, 2015
1162015
Base station activation and linear transceiver design for optimal resource management in heterogeneous networks
WC Liao, M Hong, YF Liu, ZQ Luo
IEEE Transactions on Signal Processing 62 (15), 3939-3952, 2014
1042014
Topology attack and defense for graph neural networks: An optimization perspective
K Xu, H Chen, S Liu, PY Chen, TW Weng, M Hong, X Lin
arXiv preprint arXiv:1906.04214, 2019
1032019
A distributed, asynchronous, and incremental algorithm for nonconvex optimization: an admm approach
M Hong
IEEE Transactions on Control of Network Systems 5 (3), 935-945, 2017
102*2017
Multi-agent reinforcement learning via double averaging primal-dual optimization
HT Wai, Z Yang, Z Wang, M Hong
arXiv preprint arXiv:1806.00877, 2018
1012018
Signal processing and optimal resource allocation for the interference channel
M Hong, ZQ Luo
Academic Press Library in Signal Processing 2, 409-469, 2014
912014
Linear transceiver design for a MIMO interfering broadcast channel achieving max–min fairness
M Razaviyayn, M Hong, ZQ Luo
Signal Processing 93 (12), 3327-3340, 2013
852013
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