Qing Qu

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 28

Top Topics

Convolutional Network

Subgradient Method

Diffusion Models

Top Venues

Publications

Huikang Liu, Peng Wang, Longxiu Huang, Qing Qu, Laura Balzano
Symmetric Matrix Completion with ReLU Sampling. CoRR (2024)
Avrajit Ghosh, Xitong Zhang, Kenneth K. Sun, Qing Qu, Saiprasad Ravishankar, Rongrong Wang
Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at Initialization. CoRR (2024)
Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, Qing Qu
Efficient Low-Dimensional Compression of Overparameterized Models. AISTATS (2024)
Xiang Li, Soo Min Kwon, Ismail R. Alkhouri, Saiprasad Ravishankar, Qing Qu
Decoupled Data Consistency with Diffusion Purification for Image Restoration. CoRR (2024)
Ismail Alkhouri, Shijun Liang, Rongrong Wang, Qing Qu, Saiprasad Ravishankar
Diffusion-Based Adversarial Purification for Robust Deep Mri Reconstruction. ICASSP (2024)
Peng Wang, Huikang Liu, Druv Pai, Yaodong Yu, Zhihui Zhu, Qing Qu, Yi Ma
A Global Geometric Analysis of Maximal Coding Rate Reduction. CoRR (2024)
Xiao Li, Sheng Liu, Jinxin Zhou, Xinyu Lu, Carlos Fernandez-Granda, Zhihui Zhu, Qing Qu
Understanding and Improving Transfer Learning of Deep Models via Neural Collapse. Trans. Mach. Learn. Res. 2024 (2024)
Can Yaras, Peng Wang, Laura Balzano, Qing Qu
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation. CoRR (2024)
Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency. ICLR (2024)
Shijun Liang, Evan Bell, Qing Qu, Rongrong Wang, Saiprasad Ravishankar
Analysis of Deep Image Prior and Exploiting Self-Guidance for Image Reconstruction. CoRR (2024)
Yuexiang Zhai, Shengbang Tong, Xiao Li, Mu Cai, Qing Qu, Yong Jae Lee, Yi Ma
Investigating the Catastrophic Forgetting in Multimodal Large Language Models. CoRR (2023)
Can Yaras, Peng Wang, Wei Hu, Zhihui Zhu, Laura Balzano, Qing Qu
The Law of Parsimony in Gradient Descent for Learning Deep Linear Networks. CoRR (2023)
Huijie Zhang, Yifu Lu, Ismail Alkhouri, Saiprasad Ravishankar, Dogyoon Song, Qing Qu
Improving Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architectures. CoRR (2023)
Evan Bell, Shijun Liang, Qing Qu, Saiprasad Ravishankar
Robust Self-Guided Deep Image Prior. ICASSP (2023)
Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, Qing Qu
Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics. CoRR (2023)
Peng Wang, Xiao Li, Can Yaras, Zhihui Zhu, Laura Balzano, Wei Hu, Qing Qu
Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination. CoRR (2023)
Xiang Li, Saiprasad Ravishankar, Qing Qu
Robust Deep Image Recovery from Sparsely Corrupted and Sub-Sampled Measurements. CAMSAP (2023)
Jiachen Jiang, Jinxin Zhou, Peng Wang, Qing Qu, Dustin Mixon, Chong You, Zhihui Zhu
Generalized Neural Collapse for a Large Number of Classes. CoRR (2023)
Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold. CoRR (2022)
Jinxin Zhou, Xiao Li, Tianyu Ding, Chong You, Qing Qu, Zhihui Zhu
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features. ICML (2022)
Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu
Are All Losses Created Equal: A Neural Collapse Perspective. CoRR (2022)
Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu
Are All Losses Created Equal: A Neural Collapse Perspective. NeurIPS (2022)
Xiao Li, Sheng Liu, Jinxin Zhou, Xinyu Lu, Carlos Fernandez-Granda, Zhihui Zhu, Qing Qu
Principled and Efficient Transfer Learning of Deep Models via Neural Collapse. CoRR (2022)
Sheng Liu, Zhihui Zhu, Qing Qu, Chong You
Robust Training under Label Noise by Over-parameterization. ICML (2022)
Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold. NeurIPS (2022)
Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. NeurIPS (2021)
Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu
A Geometric Analysis of Neural Collapse with Unconstrained Features. NeurIPS (2021)
Lijun Ding, Liwei Jiang, Yudong Chen, Qing Qu, Zhihui Zhu
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery. NeurIPS (2021)