Peng Wang

According to our database, Peng Wang authored at least 26 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Attention-Only Transformers via Unrolled Subspace Denoising.

Peng Wang, Yifu Lu, Yaodong Yu, Druv Pai, Qing Qu, Yi Ma

CoRR, June, 2025

Understanding Generalization in Diffusion Models via Probability Flow Distance.

Huijie Zhang, Zijian Huang, Siyi Chen, Jinfan Zhou, Zekai Zhang, Peng Wang, Qing Qu

CoRR, May, 2025

An Overview of Low-Rank Structures in the Training and Adaptation of Large Models.

Laura Balzano, Tianjiao Ding, Benjamin D. Haeffele, Soo Min Kwon, Qing Qu, Peng Wang, Zhangyang Wang, Can Yaras

CoRR, March, 2025

Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling.

Xiao Li, Zekai Zhang, Xiang Li, Siyi Chen, Zhihui Zhu, Peng Wang, Qing Qu

CoRR, February, 2025

Understanding How Nonlinear Layers Create Linearly Separable Features for Low-Dimensional Data.

Alec S. Xu, Can Yaras, Peng Wang, Qing Qu

CoRR, January, 2025

Explaining and Mitigating the Modality Gap in Contrastive Multimodal Learning.

Can Yaras, Siyi Chen, Peng Wang, Qing Qu

Proceedings of the Conference on Parsimony and Learning, 2025

2024

Diffusion Models Learn Low-Dimensional Distributions via Subspace Clustering.

Peng Wang, Huijie Zhang, Zekai Zhang, Siyi Chen, Yi Ma, Qing Qu

CoRR, 2024

Exploring Low-Dimensional Subspaces in Diffusion Models for Controllable Image Editing.

Siyi Chen, Huijie Zhang, Minzhe Guo, Yifu Lu, Peng Wang, Qing Qu

CoRR, 2024

Exploring Low-Dimensional Subspace in Diffusion Models for Controllable Image Editing.

Siyi Chen, Huijie Zhang, Minzhe Guo, Yifu Lu, Peng Wang, Qing Qu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

The Emergence of Reproducibility and Consistency in Diffusion Models.

Huijie Zhang, Jinfan Zhou, Yifu Lu, Minzhe Guo, Peng Wang, Liyue Shen, Qing Qu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation.

Can Yaras, Peng Wang, Laura Balzano, Qing Qu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Symmetric Matrix Completion with ReLU Sampling.

Huikang Liu, Peng Wang, Longxiu Huang, Qing Qu, Laura Balzano

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Generalized Neural Collapse for a Large Number of Classes.

Jiachen Jiang, Jinxin Zhou, Peng Wang, Qing Qu, Dustin G. Mixon, Chong You, Zhihui Zhu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Global Geometric Analysis of Maximal Coding Rate Reduction.

Peng Wang, Huikang Liu, Druv Pai, Yaodong Yu, Zhihui Zhu, Qing Qu, Yi Ma

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Linear Convergence of a Proximal Alternating Minimization Method with Extrapolation for \(\boldsymbol{\ell_1}\) -Norm Principal Component Analysis.

Peng Wang, Huikang Liu, Anthony Man-Cho So

SIAM J. Optim., 2023

Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination.

Peng Wang, Xiao Li, Can Yaras, Zhihui Zhu, Laura Balzano, Wei Hu, Qing Qu

CoRR, 2023

The Law of Parsimony in Gradient Descent for Learning Deep Linear Networks.

Can Yaras, Peng Wang, Wei Hu, Zhihui Zhu, Laura Balzano, Qing Qu

CoRR, 2023

Projected Tensor Power Method for Hypergraph Community Recovery.

Jinxin Wang, Yuen-Man Pun, Xiaolu Wang, Peng Wang, Anthony Man-Cho So

Proceedings of the International Conference on Machine Learning, 2023

2022

Non-convex exact community recovery in stochastic block model.

Peng Wang, Zirui Zhou, Anthony Man-Cho So

Math. Program., 2022

Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold.

Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering.

Peng Wang, Huikang Liu, Anthony Man-Cho So, Laura Balzano

Proceedings of the International Conference on Machine Learning, 2022

Exact Community Recovery over Signed Graphs.

Xiaolu Wang, Peng Wang, Anthony Man-Cho So

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method.

Peng Wang, Huikang Liu, Zirui Zhou, Anthony Man-Cho So

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

A Nearly-Linear Time Algorithm for Exact Community Recovery in Stochastic Block Model.

Peng Wang, Zirui Zhou, Anthony Man-Cho So

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Globally Convergent Accelerated Proximal Alternating Maximization Method for L1-Principal Component Analysis.

Peng Wang, Huikang Liu, Anthony Man-Cho So

Proceedings of the IEEE International Conference on Acoustics, 2019

Fast First-order Methods for the Massive Robust Multicast Beamforming Problem with Interference Temperature Constraints.

Huikang Liu, Peng Wang, Anthony Man-Cho So

Proceedings of the IEEE International Conference on Acoustics, 2019