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PENG WANG
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
标题
引用次数
引用次数
年份
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
402022
The emergence of reproducibility and consistency in diffusion models
H Zhang, J Zhou, Y Lu, M Guo, P Wang, L Shen, Q Qu
Forty-first International Conference on Machine Learning, 2023
352023
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
212021
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
152023
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
152022
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
142019
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
112023
Non-convex exact community recovery in stochastic block model
P Wang, Z Zhou, AMC So
Mathematical Programming 195 (1), 1-37, 2022
112022
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
102023
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
102020
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
92023
Exact community recovery over signed graphs
X Wang, P Wang, AMC So
International Conference on Artificial Intelligence and Statistics, 9686-9710, 2022
82022
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
62022
A Global Geometric Analysis of Maximal Coding Rate Reduction
P Wang, H Liu, D Pai, Y Yu, Z Zhu, Q Qu, Y Ma
arXiv preprint arXiv:2406.01909, 2024
42024
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
42023
Diffusion models learn low-dimensional distributions via subspace clustering
P Wang, H Zhang, Z Zhang, S Chen, Y Ma, Q Qu
arXiv preprint arXiv:2409.02426, 2024
32024
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
C Yaras, P Wang, L Balzano, Q Qu
arXiv preprint arXiv:2406.04112, 2024
32024
Symmetric Matrix Completion with ReLU Sampling
H Liu, P Wang, L Huang, Q Qu, L Balzano
arXiv preprint arXiv:2406.05822, 2024
22024
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
22023
Exploring Low-Dimensional Subspaces in Diffusion Models for Controllable Image Editing
S Chen, H Zhang, M Guo, Y Lu, P Wang, Q Qu
arXiv preprint arXiv:2409.02374, 2024
12024
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