PENG WANG

引用次数

	总计	2019 年至今
引用	155	155
h 指数	8	8
i10 指数	5	5

2019202020212022202320243 2 6 29 65 46

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Anthony Man-Cho SoDepartment of Systems Engineering and Engineering Management, The Chinese University of Hong Kong在 se.cuhk.edu.hk 的电子邮件经过验证
Qing QuAssistant Professor, Dept. of EECS, University of Michigan在 umich.edu 的电子邮件经过验证
Laura BalzanoUniversity of Michigan, Ann Arbor在 umich.edu 的电子邮件经过验证
Huikang LiuAssistant professor, Shanghai University of Finance and Economics在 se.cuhk.edu.hk 的电子邮件经过验证
Can YarasPhD Student, University of Michigan在 umich.edu 的电子邮件经过验证
Zhihui ZhuAssistant Professor, Ohio State University在 osu.edu 的电子邮件经过验证
Zirui ZhouHuawei Technologies Canada在 huawei.com 的电子邮件经过验证
Wei HuAssistant Professor of Computer Science and Engineering, University of Michigan在 umich.edu 的电子邮件经过验证
Huijie ZhangGraduate Student, University of Michigan, Ann Arbor在 umich.edu 的电子邮件经过验证
Liyue ShenUniversity of Michigan在 umich.edu 的电子邮件经过验证
Yifu LuUndergraduate, University of Michigan在 umich.edu 的电子邮件经过验证
Jinfan ZhouUniversity of Michigan在 umich.edu 的电子邮件经过验证
Xiaolu WangDepartment of ECE, The Hong Kong University of Science and Technology在 se.cuhk.edu.hk 的电子邮件经过验证
Dustin G. MixonAssociate Professor, Department of Mathematics, The Ohio State University在 osu.edu 的电子邮件经过验证
Jinxin ZhouOhio State University在 osu.edu 的电子邮件经过验证
Chong YouGoogle在 google.com 的电子邮件经过验证
Yuen-Man PunCIICADA Lab, School of Engineering, Australian National University在 anu.edu.au 的电子邮件经过验证
Jinxin WangDepartment of Systems Engineering and Engineering Management, The Chinese University of Hong Kong在 link.cuhk.edu.hk 的电子邮件经过验证
Xiao Li (李虓)Ph.D. candidate at University of Michigan在 umich.edu 的电子邮件经过验证
Taoli ZhengThe Chinese University of Hong Kong在 se.cuhk.edu.hk 的电子邮件经过验证

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PENG WANG

Postdoc Fellow, Department of Electrical Engineering and Computer Science, University of Michigan

在 umich.edu 的电子邮件经过验证 - 首页

Mathematical Optimization Algorithm Design & Analysis


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
The emergence of reproducibility and consistency in diffusion models H Zhang, J Zhou, Y Lu, M Guo, L Shen, Q Qu	28	2023
Neural collapse with normalized features: A geometric analysis over the riemannian manifold C Yaras, P Wang, Z Zhu, L Balzano, Q Qu Advances in neural information processing systems 35, 11547-11560, 2022	28	2022
Optimal non-convex exact recovery in stochastic block model via projected power method P Wang, H Liu, Z Zhou, AMC So International Conference on Machine Learning, 10828-10838, 2021	20	2021
Globally convergent accelerated proximal alternating maximization method for l1-principal component analysis P Wang, H Liu, AMC So ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019	13	2019
Linear Convergence of a Proximal Alternating Minimization Method with Extrapolation for -Norm Principal Component Analysis P Wang, H Liu, AMC So SIAM Journal on Optimization 33 (2), 684-712, 2023	12	2023
Non-convex exact community recovery in stochastic block model P Wang, Z Zhou, AMC So Mathematical Programming 195 (1), 1-37, 2022	9	2022
Linear Convergence Analysis of Neural Collapse with Unconstrained Features P Wang, H Liu, C Yaras, L Balzano, Q Qu OPT 2022: Optimization for Machine Learning (NeurIPS 2022 Workshop), 2022	9	2022
Exact community recovery over signed graphs X Wang, P Wang, AMC So International Conference on Artificial Intelligence and Statistics, 9686-9710, 2022	8	2022
A nearly-linear time algorithm for exact community recovery in stochastic block model P Wang, Z Zhou, AMC So International Conference on Machine Learning, 10126-10135, 2020	7	2020
Convergence and recovery guarantees of the k-subspaces method for subspace clustering P Wang, H Liu, AMC So, L Balzano International Conference on Machine Learning, 22884-22918, 2022	6	2022
The law of parsimony in gradient descent for learning deep linear networks C Yaras, P Wang, W Hu, Z Zhu, L Balzano, Q Qu arXiv preprint arXiv:2306.01154, 2023	5	2023
Generalized neural collapse for a large number of classes J Jiang, J Zhou, P Wang, Q Qu, D Mixon, C You, Z Zhu arXiv preprint arXiv:2310.05351, 2023	4	2023
Projected tensor power method for hypergraph community recovery J Wang, YM Pun, X Wang, P Wang, AMC So International Conference on Machine Learning, 36285-36307, 2023	3	2023
Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination P Wang, X Li, C Yaras, Z Zhu, L Balzano, W Hu, Q Qu arXiv preprint arXiv:2311.02960, 2023	2	2023
Fast first-order methods for the massive robust multicast beamforming problem with interference temperature constraints H Liu, P Wang, AMC So ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019	1	2019
Invariant Low-Dimensional Subspaces in Gradient Descent for Learning Deep Linear Networks C Yaras, P Wang, W Hu, Z Zhu, L Balzano, Q Qu Conference on Parsimony and Learning (Recent Spotlight Track), 2023		2023
Understanding Hierarchical Representations in Deep Networks via Feature Compression and Discrimination P Wang, X Li, C Yaras, Z Zhu, L Balzano, W Hu, Q Qu Conference on Parsimony and Learning (Recent Spotlight Track), 2023		2023
Invariant Low-Dimensional Subspaces in Gradient Descent for Learning Deep Matrix Factorizations C Yaras, P Wang, W Hu, Z Zhu, L Balzano, Q Qu NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning, 2023		2023
Proximal DC Algorithm for Sample Average Approximation of Chance Constrained Programming: Convergence and Numerical Results P Wang, R Jiang, Q Kong, L Balzano arXiv preprint arXiv:2301.00423, 2023		2023
A Linearly Convergent Algorithm for Rotationally Invariant -Norm Principal Component Analysis T Zheng, P Wang, AMC So arXiv preprint arXiv:2210.05066, 2022		2022

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