Zhaoqiang Liu

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 43

Top Topics

Sample Complexity

Compressive Sensing

Diffusion Models

Top Venues

Publications

Yihang Gao, Chuanyang Zheng, Enze Xie, Han Shi, Tianyang Hu, Yu Li, Michael K. Ng, Zhenguo Li, Zhaoqiang Liu
On the Expressive Power of a Variant of the Looped Transformer. CoRR (2024)
Junren Chen, Zhaoqiang Liu
Efficient Algorithms for Non-gaussian Single Index Models with Generative Priors. AAAI (2024)
Junren Chen, Zhaoqiang Liu, Meng Ding, Michael K. Ng
Uniform Recovery Guarantees for Quantized Corrupted Sensing Using Structured or Generative Priors. CoRR (2024)
Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. CoRR (2024)
Shuchen Xue, Zhaoqiang Liu, Fei Chen, Shifeng Zhang, Tianyang Hu, Enze Xie, Zhenguo Li
Accelerating Diffusion Sampling with Optimized Time Steps. CoRR (2024)
Yuanfeng Ji, Zhe Chen, Enze Xie, Lanqing Hong, Xihui Liu, Zhaoqiang Liu, Tong Lu, Zhenguo Li, Ping Luo
DDP: Diffusion Model for Dense Visual Prediction. ICCV (2023)
Enze Xie, Lewei Yao, Han Shi, Zhili Liu, Daquan Zhou, Zhaoqiang Liu, Jiawei Li, Zhenguo Li
DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuning. ICCV (2023)
Junren Chen, Shuai Huang, Michael K. Ng, Zhaoqiang Liu
Solving Quadratic Systems with Full-Rank Matrices Using Sparse or Generative Priors. CoRR (2023)
Junren Chen, Jonathan Scarlett, Michael Kwok-Po Ng, Zhaoqiang Liu
A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing. CoRR (2023)
Junren Chen, Jonathan Scarlett, Michael Ng, Zhaoqiang Liu
A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing. NeurIPS (2023)
Can Cai, Min Fan, Jing Yao, Lele Zhou, Yuanzhe Wang, Xiaoying Liang, Zhaoqiang Liu, Shu Chen
Spatial-temporal characteristics of carbon emissions corrected by socio-economic driving factors under land use changes in Sichuan Province, southwestern China. Ecol. Informatics 77 (2023)
Enze Xie, Lewei Yao, Han Shi, Zhili Liu, Daquan Zhou, Zhaoqiang Liu, Jiawei Li, Zhenguo Li
DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuning. CoRR (2023)
Yuanfeng Ji, Zhe Chen, Enze Xie, Lanqing Hong, Xihui Liu, Zhaoqiang Liu, Tong Lu, Zhenguo Li, Ping Luo
DDP: Diffusion Model for Dense Visual Prediction. CoRR (2023)
Zhaoqiang Liu, Jun Han
Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors. CoRR (2022)
Zhaoqiang Liu, Jun Han
Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors. IJCAI (2022)
Zhaoqiang Liu, Xinshao Wang, Jiulong Liu
Misspecified Phase Retrieval with Generative Priors. NeurIPS (2022)
Zhaoqiang Liu, Xinshao Wang, Jiulong Liu
Misspecified Phase Retrieval with Generative Priors. CoRR (2022)
Zhaoqiang Liu, Jiulong Liu, Subhroshekhar Ghosh, Jun Han, Jonathan Scarlett
Generative Principal Component Analysis. ICLR (2022)
Jiulong Liu, Zhaoqiang Liu
Non-Iterative Recovery from Nonlinear Observations using Generative Models. CVPR (2022)
Zhaoqiang Liu, Jiulong Liu, Subhroshekhar Ghosh, Jun Han, Jonathan Scarlett
Generative Principal Component Analysis. CoRR (2022)
Jiulong Liu, Zhaoqiang Liu
Non-Iterative Recovery from Nonlinear Observations using Generative Models. CoRR (2022)
Zhaoqiang Liu, Subhroshekhar Ghosh, Jonathan Scarlett
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors. CoRR (2021)
Zhaoqiang Liu, Subhroshekhar Ghosh, Jun Han, Jonathan Scarlett
Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors. CoRR (2021)
Zhaoqiang Liu, Subhroshekhar Ghosh, Jonathan Scarlett
Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors. NeurIPS (2021)
Zhaoqiang Liu, Subhroshekhar Ghosh, Jonathan Scarlett
Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors. ITW (2021)
Zhaoqiang Liu, Jonathan Scarlett
Sample Complexity Lower Bounds for Compressive Sensing with Generative Models. SPCOM (2020)
Zhaoqiang Liu, Jonathan Scarlett
The Generalized Lasso with Nonlinear Observations and Generative Priors. NeurIPS (2020)
Zhaoqiang Liu, Jonathan Scarlett
Information-Theoretic Lower Bounds for Compressive Sensing With Generative Models. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Zhaoqiang Liu, Jonathan Scarlett
The Generalized Lasso with Nonlinear Observations and Generative Priors. CoRR (2020)
Zhaoqiang Liu, Selwyn Gomes, Avtansh Tiwari, Jonathan Scarlett
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors. CoRR (2020)
Zhaoqiang Liu, Selwyn Gomes, Avtansh Tiwari, Jonathan Scarlett
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors. ICML (2020)
Zhaoqiang Liu
Error Bounds for Spectral Clustering over Samples from Spherical Gaussian Mixture Models. ICASSP (2019)
Zhaoqiang Liu, Vincent Y. F. Tan
The Informativeness of k-Means for Learning Mixture Models. IEEE Trans. Inf. Theory 65 (11) (2019)
Zhaoqiang Liu, Jonathan Scarlett
Information-Theoretic Lower Bounds for Compressive Sensing with Generative Models. CoRR (2019)
Zhaoqiang Liu
Model Selection for Nonnegative Matrix Factorization by Support Union Recovery. ICASSP (2019)
Zhaoqiang Liu
Model Selection for Nonnegative Matrix Factorization by Support Union Recovery. CoRR (2018)
Zhaoqiang Liu, Vincent Y. F. Tan
Rank-One NMF-Based Initialization for NMF and Relative Error Bounds Under a Geometric Assumption. ITA (2018)
Mine Alsan, Zhaoqiang Liu, Vincent Y. F. Tan
Minimax Lower Bounds for Nonnegative Matrix Factorization. SSP (2018)
Zhaoqiang Liu, Vincent Y. F. Tan
The Informativeness of k-Means for Learning Mixture Models. ISIT (2018)
Zhaoqiang Liu, Vincent Y. F. Tan
The Informativeness of k-Means for Learning Gaussian Mixture Models. CoRR (2017)
Zhaoqiang Liu, Vincent Y. F. Tan
Relative error bounds for nonnegative matrix factorization under a geometric assumption. ICASSP (2017)
Zhaoqiang Liu, Vincent Y. F. Tan
Rank-One NMF-Based Initialization for NMF and Relative Error Bounds Under a Geometric Assumption. IEEE Trans. Signal Process. 65 (18) (2017)
Zhaoqiang Liu, Vincent Y. F. Tan
Relative Error Bounds for Nonnegative Matrix Factorization under a Geometric Assumption. CoRR (2016)