Qing Qu - RankMe

121 papers A* 28A 1B 1Misc 6Journal 76Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Emergent Low-Rank Training Dynamics in MLPs with Smooth Activations. CoRR Alec S. Xu, Can Yaras, Matthew Asato, Qing Qu, Laura Balzano
2026	J	`jnl`	MCLR: Improving Conditional Modeling in Visual Generative Models via Inter-Class Likelihood-Ratio Maximization and Establishing the Equivalence between Classifier-Free Guidance and Alignment Objectives. CoRR Xiang Li, Yixuan Jia, Xiao Li, Jeffrey A. Fessler, Rongrong Wang, Qing Qu
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	J	`jnl`	Analysis of Deep Image Prior and Exploiting Self-Guidance for Image Reconstruction. IEEE Trans. Computational Imaging Shijun Liang, Evan Bell, Qing Qu, Rongrong Wang, Saiprasad Ravishankar
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`	Enhancing Video Representation Learning with Temporal Differentiation. CPAL Siyi Chen, Minkyu Choi, Zesen Zhao, Kuan Han, Qing Qu, Zhongming Liu
2025	—	`conf`	Explaining and Mitigating the Modality Gap in Contrastive Multimodal Learning. CPAL Can Yaras, Siyi Chen, Peng Wang, Qing Qu
2025	J	`jnl`	FlowDAS: A Flow-Based Framework for Data Assimilation. CoRR Siyi Chen, Yixuan Jia, Qing Qu, He Sun, Jeffrey A. Fessler
2025	J	`jnl`	Generalization of Diffusion Models Arises with a Balanced Representation Space. CoRR Zekai Zhang, Xiao Li, Xiang Li, Lianghe Shi, Meng Wu, Molei Tao, Qing Qu
2025	J	`jnl`	Learning Dynamics of Deep Linear Networks Beyond the Edge of Stability. CoRR Avrajit Ghosh, Soo Min Kwon, Rongrong Wang, Saiprasad Ravishankar, Qing Qu
2025	A*	`conf`	Learning Dynamics of Deep Matrix Factorization Beyond the Edge of Stability. ICLR Avrajit Ghosh, Soo Min Kwon, Rongrong Wang, Saiprasad Ravishankar, Qing Qu
2025	—	`conf`	Network-Regularized Diffusion Sampling For 3D Computed Tomography. CAMSAP Shijun Liang, Ismail Alkhouri, Qing Qu, Rongrong Wang, Saiprasad Ravishankar
2025	J	`jnl`	Out-of-Distribution Generalization of In-Context Learning: A Low-Dimensional Subspace Perspective. CoRR Soo Min Kwon, Alec S. Xu, Can Yaras, Laura Balzano, Qing Qu
2025	A*	`conf`	SITCOM: Step-wise Triple-Consistent Diffusion Sampling For Inverse Problems. ICML Ismail Alkhouri, Shijun Liang, Cheng-Han Huang, Jimmy Dai, Qing Qu, Saiprasad Ravishankar, Rongrong Wang
2025	Misc	`conf`	Sequential Diffusion-Guided Deep Image Prior for Medical Image Reconstruction. ICASSP Shijun Liang, Ismail Alkhouri, Qing Qu, Rongrong Wang, Saiprasad Ravishankar
2025	J	`jnl`	The Dual Power of Interpretable Token Embeddings: Jailbreaking Attacks and Defenses for Diffusion Model Unlearning. CoRR Siyi Chen, Yimeng Zhang, Sijia Liu, Qing Qu
2025	J	`jnl`	Towards Understanding the Mechanisms of Classifier-Free Guidance. CoRR Xiang Li, Rongrong Wang, Qing Qu
2025	J	`jnl`	UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights. CoRR Shijun Liang, Ismail R. Alkhouri, Siddhant Gautam, Qing Qu, Saiprasad Ravishankar
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
2025	J	`jnl`	Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs. CoRR Yiwei Chen, Soumyadeep Pal, Yimeng Zhang, Qing Qu, Sijia Liu
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	J	`jnl`	Analysis of Deep Image Prior and Exploiting Self-Guidance for Image Reconstruction. CoRR Shijun Liang, Evan Bell, Qing Qu, Rongrong Wang, Saiprasad Ravishankar
2024	J	`jnl`	Analyzing and Improving Model Collapse in Rectified Flow Models. CoRR Huminhao Zhu, Fangyikang Wang, Tianyu Ding, Qing Qu, Zhihui Zhu
2024	A*	`conf`	BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference. NeurIPS Changwoo Lee, Soo Min Kwon, Qing Qu, Hun-Seok Kim
2024	J	`jnl`	BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference. CoRR Changwoo Lee, Soo Min Kwon, Qing Qu, Hun-Seok Kim
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`	Decoupled Data Consistency with Diffusion Purification for Image Restoration. CoRR Xiang Li, Soo Min Kwon, Ismail R. Alkhouri, Saiprasad Ravishankar, 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	Misc	`conf`	Diffusion-Based Adversarial Purification for Robust Deep Mri Reconstruction. ICASSP Ismail Alkhouri, Shijun Liang, Rongrong Wang, Qing Qu, Saiprasad Ravishankar
2024	A	`conf`	Efficient Low-Dimensional Compression of Overparameterized Models. AISTATS Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, 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`	Image Reconstruction Via Autoencoding Sequential Deep Image Prior. NeurIPS Ismail Alkhouri, Shijun Liang, Evan Bell, Qing Qu, Rongrong Wang, Saiprasad Ravishankar
2024	A*	`conf`	Improving Training Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architecture. CVPR Huijie Zhang, Yifu Lu, Ismail Alkhouri, Saiprasad Ravishankar, Dogyoon Song, Qing Qu
2024	—	`conf`	Investigating the Catastrophic Forgetting in Multimodal Large Language Model Fine-Tuning. CPAL Yuexiang Zhai, Shengbang Tong, Xiao Li, Mu Cai, Qing Qu, Yong Jae Lee, Yi Ma
2024	A*	`conf`	Neural Collapse in Multi-label Learning with Pick-all-label Loss. ICML Pengyu Li, Xiao Li, Yutong Wang, Qing Qu
2024	J	`jnl`	Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at Initialization. CoRR Avrajit Ghosh, Xitong Zhang, Kenneth K. Sun, Qing Qu, Saiprasad Ravishankar, Rongrong Wang
2024	A*	`conf`	Optimal Eye Surgeon: Finding image priors through sparse generators at initialization. ICML Avrajit Ghosh, Xitong Zhang, Kenneth K. Sun, Qing Qu, Saiprasad Ravishankar, Rongrong Wang
2024	J	`jnl`	SITCOM: Step-wise Triple-Consistent Diffusion Sampling for Inverse Problems. CoRR Ismail Alkhouri, Shijun Liang, Cheng-Han Huang, Jimmy Dai, Qing Qu, Saiprasad Ravishankar, Rongrong Wang
2024	J	`jnl`	Shallow Diffuse: Robust and Invisible Watermarking through Low-Dimensional Subspaces in Diffusion Models. CoRR Wenda Li, Huijie Zhang, Qing Qu
2024	J	`jnl`	Sim2Real in Reconstructive Spectroscopy: Deep Learning with Augmented Device-Informed Data Simulation. CoRR Jiyi Chen, Pengyu Li, Yutong Wang, Pei-Cheng Ku, Qing Qu
2024	A*	`conf`	Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency. ICLR Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
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
2024	A*	`conf`	Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure. NeurIPS Xiang Li, Yixiang Dai, Qing Qu
2024	J	`jnl`	Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure. CoRR Xiang Li, Yixiang Dai, Qing Qu
2024	J	`jnl`	Understanding and Improving Transfer Learning of Deep Models via Neural Collapse. Trans. Mach. Learn. Res. Xiao Li, Sheng Liu, Jinxin Zhou, Xinyu Lu, Carlos Fernandez-Granda, Zhihui Zhu, Qing Qu
2024	J	`jnl`	Unfolding Videos Dynamics via Taylor Expansion. CoRR Siyi Chen, Minkyu Choi, Zesen Zhao, Kuan Han, Qing Qu, Zhongming Liu
2023	J	`jnl`	Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics. CoRR Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, 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`	Improving Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architectures. CoRR Huijie Zhang, Yifu Lu, Ismail Alkhouri, Saiprasad Ravishankar, Dogyoon Song, Qing Qu
2023	J	`jnl`	Investigating the Catastrophic Forgetting in Multimodal Large Language Models. CoRR Yuexiang Zhai, Shengbang Tong, Xiao Li, Mu Cai, Qing Qu, Yong Jae Lee, Yi Ma
2023	J	`jnl`	Neural Collapse in Multi-label Learning with Pick-all-label Loss. CoRR Pengyu Li, Yutong Wang, Xiao Li, Qing Qu
2023	—	`conf`	Robust Deep Image Recovery from Sparsely Corrupted and Sub-Sampled Measurements. CAMSAP Xiang Li, Saiprasad Ravishankar, Qing Qu
2023	Misc	`conf`	Robust Self-Guided Deep Image Prior. ICASSP Evan Bell, Shijun Liang, Qing Qu, Saiprasad Ravishankar
2023	J	`jnl`	Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency. CoRR Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
2023	J	`jnl`	The Emergence of Reproducibility and Consistency in Diffusion Models. CoRR Huijie Zhang, Jinfan Zhou, Yifu Lu, Minzhe Guo, Liyue Shen, Qing Qu
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`	Are All Losses Created Equal: A Neural Collapse Perspective. NeurIPS Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu
2022	J	`jnl`	Are All Losses Created Equal: A Neural Collapse Perspective. CoRR Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu
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	A*	`conf`	On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features. ICML Jinxin Zhou, Xiao Li, Tianyu Ding, Chong You, Qing Qu, Zhihui Zhu
2022	J	`jnl`	On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features. CoRR Jinxin Zhou, Xiao Li, Tianyu Ding, Chong You, Qing Qu, Zhihui Zhu
2022	J	`jnl`	Principled and Efficient Transfer Learning of Deep Models via Neural Collapse. CoRR Xiao Li, Sheng Liu, Jinxin Zhou, Xinyu Lu, Carlos Fernandez-Granda, Zhihui Zhu, Qing Qu
2022	A*	`conf`	Robust Training under Label Noise by Over-parameterization. ICML Sheng Liu, Zhihui Zhu, Qing Qu, Chong You
2022	J	`jnl`	Robust Training under Label Noise by Over-parameterization. CoRR Sheng Liu, Zhihui Zhu, Qing Qu, Chong You
2021	A*	`conf`	A Geometric Analysis of Neural Collapse with Unconstrained Features. NeurIPS Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu
2021	J	`jnl`	A Geometric Analysis of Neural Collapse with Unconstrained Features. CoRR Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu
2021	A*	`conf`	Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. NeurIPS Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu
2021	J	`jnl`	Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training. CoRR Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu
2021	A*	`conf`	Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery. NeurIPS Lijun Ding, Liwei Jiang, Yudong Chen, Qing Qu, Zhihui Zhu
2021	J	`jnl`	Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery. CoRR Lijun Ding, Liwei Jiang, Yudong Chen, Qing Qu, Zhihui Zhu
2021	J	`jnl`	Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods. SIAM J. Optim. Xiao Li, Shixiang Chen, Zengde Deng, Qing Qu, Zhihui Zhu, Anthony Man-Cho So
2020	J	`jnl`	Convolutional Phase Retrieval via Gradient Descent. IEEE Trans. Inf. Theory Qing Qu, Yuqian Zhang, Yonina C. Eldar, John Wright
2020	J	`jnl`	Exact Recovery of Multichannel Sparse Blind Deconvolution via Gradient Descent. SIAM J. Imaging Sci. Qing Qu, Xiao Li, Zhihui Zhu
2020	J	`jnl`	Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications. CoRR Qing Qu, Zhihui Zhu, Xiao Li, Manolis C. Tsakiris, John Wright, René Vidal
2020	J	`jnl`	From Symmetry to Geometry: Tractable Nonconvex Problems. CoRR Yuqian Zhang, Qing Qu, John Wright
2020	A*	`conf`	Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning. ICLR Qing Qu, Yuexiang Zhai, Xiao Li, Yuqian Zhang, Zhihui Zhu
2020	A*	`conf`	Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization. NeurIPS Chong You, Zhihui Zhu, Qing Qu, Yi Ma
2020	J	`jnl`	Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization. CoRR Chong You, Zhihui Zhu, Qing Qu, Yi Ma
2020	A*	`conf`	Short and Sparse Deconvolution - A Geometric Approach. ICLR Yenson Lau, Qing Qu, Han-Wen Kuo, Pengcheng Zhou, Yuqian Zhang, John Wright
2019	A*	`conf`	A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution. NeurIPS Qing Qu, Xiao Li, Zhihui Zhu
2019	J	`jnl`	A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution. CoRR Qing Qu, Xiao Li, Zhihui Zhu
2019	J	`jnl`	Analysis of the Optimization Landscapes for Overcomplete Representation Learning. CoRR Qing Qu, Yuexiang Zhai, Xiao Li, Yuqian Zhang, Zhihui Zhu
2019	Misc	`conf`	Exact and Efficient Multi-Channel Sparse Blind Deconvolution - A Nonconvex Approach. ACSSC Qing Qu, Xiao Li, Zhihui Zhu
2019	J	`jnl`	Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods. CoRR Xiao Li, Shixiang Chen, Zengde Deng, Qing Qu, Zhihui Zhu, Anthony Man-Cho So
2019	J	`jnl`	Short-and-Sparse Deconvolution - A Geometric Approach. CoRR Yenson Lau, Qing Qu, Han-Wen Kuo, Pengcheng Zhou, Yuqian Zhang, John Wright
2018	J	`jnl`	A Geometric Analysis of Phase Retrieval. Found. Comput. Math. Ju Sun, Qing Qu, John Wright
2017	J	`jnl`	Complete Dictionary Recovery Over the Sphere I: Overview and the Geometric Picture. IEEE Trans. Inf. Theory Ju Sun, Qing Qu, John Wright
2017	J	`jnl`	Complete Dictionary Recovery Over the Sphere II: Recovery by Riemannian Trust-Region Method. IEEE Trans. Inf. Theory Ju Sun, Qing Qu, John Wright
2017	J	`jnl`	Convolutional Phase Retrieval via Gradient Descent. CoRR Qing Qu, Yuqian Zhang, Yonina C. Eldar, John Wright
2017	—	`conf`	Convolutional Phase Retrieval. NIPS Qing Qu, Yuqian Zhang, Yonina C. Eldar, John Wright
2016	J	`jnl`	A Geometric Analysis of Phase Retrieval. CoRR Ju Sun, Qing Qu, John Wright
2016	B	`conf`	A geometric analysis of phase retrieval. ISIT Ju Sun, Qing Qu, John Wright
2016	J	`jnl`	Finding a Sparse Vector in a Subspace: Linear Sparsity Using Alternating Directions. IEEE Trans. Inf. Theory Qing Qu, Ju Sun, John Wright
2015	A*	`conf`	Complete Dictionary Recovery Using Nonconvex Optimization. ICML Ju Sun, Qing Qu, John Wright
2015	J	`jnl`	Complete Dictionary Recovery over the Sphere I: Overview and the Geometric Picture. CoRR Ju Sun, Qing Qu, John Wright
2015	J	`jnl`	Complete Dictionary Recovery over the Sphere II: Recovery by Riemannian Trust-region Method. CoRR Ju Sun, Qing Qu, John Wright
2015	J	`jnl`	Complete Dictionary Recovery over the Sphere. CoRR Ju Sun, Qing Qu, John Wright
2015	J	`jnl`	Subspace Vertex Pursuit: A Fast and Robust Near-Separable Nonnegative Matrix Factorization Method for Hyperspectral Unmixing. IEEE J. Sel. Top. Signal Process. Qing Qu, Nasser M. Nasrabadi, Trac D. Tran
2015	J	`jnl`	When Are Nonconvex Problems Not Scary? CoRR Ju Sun, Qing Qu, John Wright
2014	J	`jnl`	Abundance Estimation for Bilinear Mixture Models via Joint Sparse and Low-Rank Representation. IEEE Trans. Geosci. Remote. Sens. Qing Qu, Nasser M. Nasrabadi, Trac D. Tran
2014	—	`conf`	Finding a sparse vector in a subspace: Linear sparsity using alternating directions. NIPS Qing Qu, Ju Sun, John Wright
2014	J	`jnl`	Finding a sparse vector in a subspace: Linear sparsity using alternating directions. CoRR Qing Qu, Ju Sun, John Wright
2014	J	`jnl`	Structured Priors for Sparse-Representation-Based Hyperspectral Image Classification. CoRR Xiaoxia Sun, Qing Qu, Nasser M. Nasrabadi, Trac D. Tran
2014	J	`jnl`	Structured Priors for Sparse-Representation-Based Hyperspectral Image Classification. IEEE Geosci. Remote. Sens. Lett. Xiaoxia Sun, Qing Qu, Nasser M. Nasrabadi, Trac D. Tran
2014	Misc	`conf`	Subspace vertex pursuit for separable non-negative matrix factorization in hyperspectral unmixing. ICASSP Qing Qu, Xiaoxia Sun, Nasser M. Nasrabadi, Trac D. Tran
2013	Misc	`conf`	Hyperspectral abundance estimation for the generalized bilinear model with joint sparsity constraint. ICASSP Qing Qu, Nasser M. Nasrabadi, Trac D. Tran
2013	—	`conf`	Low rank representation for bilinear abundance estimation problem. WHISPERS Qing Qu, Xiaoxia Sun, Nasser M. Nasrabadi, Trac D. Tran