Separation-Free Super-Resolution from Compressed Measurements is Possible: an Orthonormal Atomic Norm Minimization Approach. - Weiyu Xu; Jirong Yi; Soura Dasgupta; Jian-Feng Cai 001; Mathews Jacob; Myung Cho (CoRR, 2017)

Sep]ration-Free Super-Resolution from Compressed Measurements is Possible: an Orthonormal Atomic Norm Minimization Approach. - Weiyu Xu; Jirong Yi; Soura Dasgupta; Jian-Feng Cai 001; Mathews Jacob; Myung Cho (ISIT, 2018)

Outlier Detection using Generative Models with Theoretical Performance Guarantees. - Jirong Yi; Anh Duc Le; Tianming Wang; Xiaodong Wu 001; Weiyu Xu (CoRR, 2018)

An Information-Theoretic Explanation for the Adversarial Fragility of AI Classifiers. - Hui Xie; Jirong Yi; Weiyu Xu; Raghu Mudumbai (ISIT, 2019)

Joint 3D UAV Placement and Resource Allocation in Software-Defined Cellular Networks With Wireless Backhaul. - Chunyu Pan; Jirong Yi; Changchuan Yin; Jian Yu; Xuehua Li (IEEE Access, 2019)

Trust but Verify: An Information-Theoretic Explanation for the Adversarial Fragility of Machine Learning Systems, and a General Defense against Adversarial Attacks. - Jirong Yi; Hui Xie; Leixin Zhou; Xiaodong Wu 001; Weiyu Xu; Raghuraman Mudumbai (CoRR, 2019)

Do Deep Minds Think Alike? Selective Adversarial Attacks for Fine-Grained Manipulation of Multiple Deep Neural Networks. - Zain Khan; Jirong Yi; Raghu Mudumbai; Xiaodong Wu 001; Weiyu Xu (CoRR, 2020)

Low-Cost and High-Throughput Testing of COVID-19 Viruses and Antibodies via Compressed Sensing: System Concepts and Computational Experiments. - Jirong Yi; Raghu Mudumbai; Weiyu Xu (CoRR, 2020)

Optimal Pooling Matrix Design for Group Testing with Dilution (Row Degree) Constraints. - Jirong Yi; Myung Cho; Xiaodong Wu 001; Raghu Mudumbai; Weiyu Xu (CoRR, 2020)

Necessary and Sufficient Null Space Condition for Nuclear Norm Minimization in Low-Rank Matrix Recovery. - Jirong Yi; Weiyu Xu (IEEE Trans. Inf. Theory, 2020)

Solving Large Scale Quadratic Constrained Basis Pursuit. - Jirong Yi (CoRR, 2021)

Mutual Information Learned Classifiers: an Information-theoretic Viewpoint of Training Deep Learning Classification Systems. - Jirong Yi; Qiaosheng Zhang; Zhen Chen; Qiao Liu 008; Wei Shao (CoRR, 2022)

Mutual Information Learned Regressor: an Information-theoretic Viewpoint of Training Regression Systems. - Jirong Yi; Qiaosheng Zhang; Zhen Chen; Qiao Liu 008; Wei Shao; Yusen He; Yaohua Wang (CoRR, 2022)

Use of compressed sensing to expedite high-throughput diagnostic testing for COVID-19 and beyond. - Kody A. Waldstein; Jirong Yi; Myung Cho; Raghu Mudumbai; Xiaodong Wu 001; Steven M. Varga; Weiyu Xu (PLoS Comput. Biol., 2022)

Error Correction Codes for Testing Chemical/Biological Agents: Using Pooled Testing to Increase Test Reliability. - Jirong Yi; Myung Cho; Jingchao Gao; Xiaodong Wu 001; Weiyu Xu; Raghu Mudumbai (ACSSC, 2023)

Outlier Detection for Generative Models with Performance Guarantees. - Jingchao Gao; Jirong Yi; Weiyu Xu (CISS, 2023)

Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning. - Jirong Yi; Raghu Mudumbai; Weiyu Xu (IEEECONF, 2024)

Towards unlocking the mystery of adversarial fragility of neural networks. - Jingchao Gao; Raghu Mudumbai; Xiaodong Wu 001; Jirong Yi; Catherine Xu; Hui Xie; Weiyu Xu (CoRR, 2024)

Outlier Detection Using Generative Models With Theoretical Performance Guarantees. - Jirong Yi; Jingchao Gao; Tianming Wang; Xiaodong Wu 001; Weiyu Xu (IEEE Trans. Inf. Theory, 2025)