Peng Wang - RankMe

37 papers A* 12A 1Misc 2Journal 20Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Proximal Difference-of-Convex Algorithm for Sample Average Approximation of Chance Constrained Programming. INFORMS J. Comput. Peng Wang, Rujun Jiang, Qingyuan Kong, Laura Balzano
2025	J	`jnl`	An Overview of Low-Rank Structures in the Training and Adaptation of Large Models. CoRR Laura Balzano, Tianjiao Ding, Benjamin D. Haeffele, Soo Min Kwon, Qing Qu, Peng Wang, Zhangyang Wang, Can Yaras
2025	A*	`conf`	Attention-Only Transformers via Unrolled Subspace Denoising. ICML Peng Wang, Yifu Lu, Yaodong Yu, Druv Pai, Qing Qu, Yi Ma
2025	J	`jnl`	Attention-Only Transformers via Unrolled Subspace Denoising. CoRR Peng Wang, Yifu Lu, Yaodong Yu, Druv Pai, Qing Qu, Yi Ma
2025	—	`conf`	Diffusion Models Learn Low-Dimensional Distributions VIA Subspace Clustering. CAMSAP Peng Wang, Huijie Zhang, Zekai Zhang, Siyi Chen, Yi Ma, Qing Qu
2025	—	`conf`	Explaining and Mitigating the Modality Gap in Contrastive Multimodal Learning. CPAL Can Yaras, Siyi Chen, Peng Wang, Qing Qu
2025	J	`jnl`	Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination. J. Mach. Learn. Res. Peng Wang, Xiao Li, Can Yaras, Zhihui Zhu, Laura Balzano, Wei Hu, Qing Qu
2025	J	`jnl`	Understanding Generalization in Diffusion Models via Probability Flow Distance. CoRR Huijie Zhang, Zijian Huang, Siyi Chen, Jinfan Zhou, Zekai Zhang, Peng Wang, Qing Qu
2025	J	`jnl`	Understanding How Nonlinear Layers Create Linearly Separable Features for Low-Dimensional Data. CoRR Alec S. Xu, Can Yaras, Peng Wang, Qing Qu
2025	J	`jnl`	Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling. CoRR Xiao Li, Zekai Zhang, Xiang Li, Siyi Chen, Zhihui Zhu, Peng Wang, Qing Qu
2024	A*	`conf`	A Global Geometric Analysis of Maximal Coding Rate Reduction. ICML Peng Wang, Huikang Liu, Druv Pai, Yaodong Yu, Zhihui Zhu, Qing Qu, Yi Ma
2024	J	`jnl`	A Global Geometric Analysis of Maximal Coding Rate Reduction. CoRR Peng Wang, Huikang Liu, Druv Pai, Yaodong Yu, Zhihui Zhu, Qing Qu, Yi Ma
2024	A*	`conf`	Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation. ICML Can Yaras, Peng Wang, Laura Balzano, Qing Qu
2024	J	`jnl`	Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation. CoRR Can Yaras, Peng Wang, Laura Balzano, Qing Qu
2024	J	`jnl`	Diffusion Models Learn Low-Dimensional Distributions via Subspace Clustering. CoRR Peng Wang, Huijie Zhang, Zekai Zhang, Siyi Chen, Yi Ma, Qing Qu
2024	J	`jnl`	Explaining and Mitigating the Modality Gap in Contrastive Multimodal Learning. CoRR Can Yaras, Siyi Chen, Peng Wang, Qing Qu
2024	A*	`conf`	Exploring Low-Dimensional Subspace in Diffusion Models for Controllable Image Editing. NeurIPS Siyi Chen, Huijie Zhang, Minzhe Guo, Yifu Lu, Peng Wang, Qing Qu
2024	J	`jnl`	Exploring Low-Dimensional Subspaces in Diffusion Models for Controllable Image Editing. CoRR Siyi Chen, Huijie Zhang, Minzhe Guo, Yifu Lu, Peng Wang, Qing Qu
2024	A*	`conf`	Generalized Neural Collapse for a Large Number of Classes. ICML Jiachen Jiang, Jinxin Zhou, Peng Wang, Qing Qu, Dustin G. Mixon, Chong You, Zhihui Zhu
2024	A*	`conf`	Symmetric Matrix Completion with ReLU Sampling. ICML Huikang Liu, Peng Wang, Longxiu Huang, Qing Qu, Laura Balzano
2024	J	`jnl`	Symmetric Matrix Completion with ReLU Sampling. CoRR Huikang Liu, Peng Wang, Longxiu Huang, Qing Qu, Laura Balzano
2024	A*	`conf`	The Emergence of Reproducibility and Consistency in Diffusion Models. ICML Huijie Zhang, Jinfan Zhou, Yifu Lu, Minzhe Guo, Peng Wang, Liyue Shen, Qing Qu
2023	J	`jnl`	Generalized Neural Collapse for a Large Number of Classes. CoRR Jiachen Jiang, Jinxin Zhou, Peng Wang, Qing Qu, Dustin G. Mixon, Chong You, Zhihui Zhu
2023	J	`jnl`	Linear Convergence of a Proximal Alternating Minimization Method with Extrapolation for \(\boldsymbol{\ell_1}\) -Norm Principal Component Analysis. SIAM J. Optim. Peng Wang, Huikang Liu, Anthony Man-Cho So
2023	A*	`conf`	Projected Tensor Power Method for Hypergraph Community Recovery. ICML Jinxin Wang, Yuen-Man Pun, Xiaolu Wang, Peng Wang, Anthony Man-Cho So
2023	J	`jnl`	The Law of Parsimony in Gradient Descent for Learning Deep Linear Networks. CoRR Can Yaras, Peng Wang, Wei Hu, Zhihui Zhu, Laura Balzano, Qing Qu
2023	J	`jnl`	Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination. CoRR Peng Wang, Xiao Li, Can Yaras, Zhihui Zhu, Laura Balzano, Wei Hu, Qing Qu
2022	A*	`conf`	Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering. ICML Peng Wang, Huikang Liu, Anthony Man-Cho So, Laura Balzano
2022	A	`conf`	Exact Community Recovery over Signed Graphs. AISTATS Xiaolu Wang, Peng Wang, Anthony Man-Cho So
2022	J	`jnl`	Exact Community Recovery over Signed Graphs. CoRR Xiaolu Wang, Peng Wang, Anthony Man-Cho So
2022	A*	`conf`	Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold. NeurIPS Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu
2022	J	`jnl`	Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold. CoRR Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu
2022	J	`jnl`	Non-convex exact community recovery in stochastic block model. Math. Program. Peng Wang, Zirui Zhou, Anthony Man-Cho So
2021	A*	`conf`	Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method. ICML Peng Wang, Huikang Liu, Zirui Zhou, Anthony Man-Cho So
2020	A*	`conf`	A Nearly-Linear Time Algorithm for Exact Community Recovery in Stochastic Block Model. ICML Peng Wang, Zirui Zhou, Anthony Man-Cho So
2019	Misc	`conf`	Fast First-order Methods for the Massive Robust Multicast Beamforming Problem with Interference Temperature Constraints. ICASSP Huikang Liu, Peng Wang, Anthony Man-Cho So
2019	Misc	`conf`	Globally Convergent Accelerated Proximal Alternating Maximization Method for L1-Principal Component Analysis. ICASSP Peng Wang, Huikang Liu, Anthony Man-Cho So