Követés
PENG WANG
PENG WANG
Postdoc Fellow, Department of Electrical Engineering and Computer Science, University of Michigan
E-mail megerősítve itt: umich.edu - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
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
352022
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
322023
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 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
142022
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
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
122023
Non-convex exact community recovery in stochastic block model
P Wang, Z Zhou, AMC So
Mathematical Programming 195 (1), 1-37, 2022
112022
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
72023
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
72023
Exact community recovery over signed graphs
X Wang, P Wang, AMC So
International Conference on Artificial Intelligence and Statistics, 9686-9710, 2022
72022
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
62023
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
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
32023
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
Symmetric Matrix Completion with ReLU Sampling
H Liu, P Wang, L Huang, Q Qu, L Balzano
arXiv preprint arXiv:2406.05822, 2024
12024
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
12024
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
12019
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
C Yaras, P Wang, L Balzano, Q Qu
arXiv preprint arXiv:2406.04112, 2024
2024
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
A rendszer jelenleg nem tudja elvégezni a műveletet. Próbálkozzon újra később.
Cikkek 1–20