Jiaxi Ying

According to our database, Jiaxi Ying authored at least 30 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Polynomial Graphical Lasso: Learning Edges from Gaussian Graph-Stationary Signals.

Andrei Buciulea, Jiaxi Ying, Antonio G. Marques, Daniel P. Palomar

CoRR, 2024

A Fast and Provable Algorithm for Sparse Phase Retrieval.

Jian-Feng Cai, Yu Long, Ruixue Wen, Jiaxi Ying

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

A nested tensor-based receiver employing triple constellation precoding for three-hop cooperative communication systems.

Xi Han, Jiaxi Ying, An Liu, Li Ma

Digit. Signal Process., March, 2023

Efficient and Scalable Parametric High-Order Portfolios Design via the Skew-$t$ Distribution.

Xiwen Wang, Rui Zhou, Jiaxi Ying, Daniel P. Palomar

IEEE Trans. Signal Process., 2023

Network Topology Inference with Sparsity and Laplacian Constraints.

Jiaxi Ying, Xi Han, Rui Zhou, Xiwen Wang, Hing Cheung So

CoRR, 2023

Learning Large-Scale MTP₂ Gaussian Graphical Models via Bridge-Block Decomposition.

Xiwen Wang, Jiaxi Ying, Daniel P. Palomar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity.

Jianfeng Cai, José Vinícius de Miranda Cardoso, Daniel P. Palomar, Jiaxi Ying

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptive Estimation of Graphical Models under Total Positivity.

Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar

Proceedings of the International Conference on Machine Learning, 2023

Estimating Normalized Graph Laplacians in Financial Markets.

José Vinícius de Miranda Cardoso, Jiaxi Ying, Sandeep Kumar, Daniel P. Palomar

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Tensor-Based Information Monitoring Receiver in UAV-Aided MIMO Communication Systems.

Xi Han, Xinyuan Zhao, Jiaxi Ying, Feifei Gao

IEEE Wirel. Commun. Lett., 2022

Covariance Matrix Estimation Under Low-Rank Factor Model With Nonnegative Correlations.

Rui Zhou, Jiaxi Ying, Daniel P. Palomar

IEEE Trans. Signal Process., 2022

Adaptive Estimation of MTP₂ Graphical Models.

Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar

CoRR, 2022

Learning Bipartite Graphs: Heavy Tails and Multiple Components.

José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel P. Palomar

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient Algorithms for General Isotone Optimization.

Xiwen Wang, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Semi-Blind Receivers for UAV M-KRST Coding MIMO Systems Based on Nested Tensor Models.

Xi Han, Yuyu Zhao, Jiaxi Ying

IEEE Wirel. Commun. Lett., 2021

Fast Projected Newton-like Method for Precision Matrix Estimation with Nonnegative Partial Correlations.

Jiaxi Ying, José Vinícius de Miranda Cardoso, Jian-Feng Cai, Daniel P. Palomar

CoRR, 2021

Graphical Models in Heavy-Tailed Markets.

José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel P. Palomar

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Minimax Estimation of Laplacian Constrained Precision Matrices.

Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

A Fast Algorithm for Graph Learning under Attractive Gaussian Markov Random Fields.

Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020

A Unified Framework for Structured Graph Learning via Spectral Constraints.

Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar

J. Mach. Learn. Res., 2020

Algorithms for Learning Graphs in Financial Markets.

José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel Pérez Palomar

CoRR, 2020

Does the 𝓁₁-norm Learn a Sparse Graph under Laplacian Constrained Graphical Models?

Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar

CoRR, 2020

Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model.

Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Structured Graph Learning Via Laplacian Spectral Constraints.

Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bipartite Structured Gaussian Graphical Modeling via Adjacency Spectral Priors.

Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

Vandermonde Factorization of Hankel Matrix for Complex Exponential Signal Recovery - Application in Fast NMR Spectroscopy.

Jiaxi Ying, Jian-Feng Cai, Di Guo, Gongguo Tang, Zhong Chen, Xiaobo Qu

IEEE Trans. Signal Process., 2018

Low Rank Enhanced Matrix Recovery of Hybrid Time and Frequency Data in Fast Magnetic Resonance Spectroscopy.

Hengfa Lu, Xinlin Zhang, Tianyu Qiu, Jian Yang, Jiaxi Ying, Di Guo, Zhong Chen, Xiaobo Qu

IEEE Trans. Biomed. Eng., 2018

Multi-Contrast Brain MRI Image Super-Resolution With Gradient-Guided Edge Enhancement.

Hong Zheng, Kun Zeng, Di Guo, Jiaxi Ying, Yu Yang, Xi Peng, Feng Huang, Zhong Chen, Xiaobo Qu

IEEE Access, 2018

2017

Hankel Matrix Nuclear Norm Regularized Tensor Completion for N-dimensional Exponential Signals.

Jiaxi Ying, Hengfa Lu, Qingtao Wei, Jian-Feng Cai, Di Guo, Jihui Wu, Zhong Chen, Xiaobo Qu

IEEE Trans. Signal Process., 2017

Accelerated magnetic resonance spectroscopy with Vandermonde factorization.

Xiaobo Qu, Jiaxi Ying, Jian-Feng Cai, Zhong Chen

Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017