| Pattern-coupled sparse Bayesian learning for recovery of block-sparse signals J Fang, Y Shen, H Li, P Wang IEEE Transactions on Signal Processing 63 (2), 360-372, 2014 | 252 | 2014 |
| Super-Resolution Compressed Sensing for Line Spectral Estimation: An Iterative Reweighted Approach J Fang, F Wang, Y Shen, H Li, R Blum IEEE Transactions on Signal Processing 64 (18), 4649-4662, 2016 | 200 | 2016 |
| Topology identification and learning over graphs: Accounting for nonlinearities and dynamics GB Giannakis, Y Shen, GV Karanikolas Proceedings of the IEEE 106 (5), 787-807, 2018 | 199 | 2018 |
| Kernel-based structural equation models for topology identification of directed networks Y Shen, B Baingana, GB Giannakis IEEE Transactions on Signal Processing 65 (10), 2503-2516, 2017 | 123* | 2017 |
| Nonlinear structural vector autoregressive models with application to directed brain networks Y Shen, GB Giannakis, B Baingana IEEE Transactions on Signal Processing 67 (20), 5325-5339, 2019 | 86* | 2019 |
| Super-resolution compressed sensing: An iterative reweighted algorithm for joint parameter learning and sparse signal recovery J Fang, J Li, Y Shen, H Li, S Li IEEE Signal Processing Letters 21 (6), 761-765, 2014 | 84 | 2014 |
| Tensor decompositions for identifying directed graph topologies and tracking dynamic networks Y Shen, B Baingana, GB Giannakis IEEE Transactions on Signal Processing 65 (14), 3675-3687, 2017 | 80 | 2017 |
| Random feature-based online multi-kernel learning in environments with unknown dynamics Y Shen, T Chen, GB Giannakis Journal of Machine Learning Research 20 (22), 1-36, 2019 | 77 | 2019 |
| Semi-blind inference of topologies and dynamical processes over dynamic graphs VN Ioannidis, Y Shen, GB Giannakis IEEE Transactions on Signal Processing 67 (9), 2263-2274, 2019 | 70 | 2019 |
| Exact reconstruction analysis of log-sum minimization for compressed sensing Y Shen, J Fang, H Li Signal Processing Letters 20 (12), 1223-1226, 2013 | 69 | 2013 |
| Online multi-agent forecasting with interpretable collaborative graph neural networks M Li, S Chen, Y Shen, G Liu, IW Tsang, Y Zhang IEEE Transactions on Neural Networks and Learning Systems 35 (4), 4768-4782, 2022 | 58 | 2022 |
| Canonical correlation analysis of datasets with a common source graph J Chen, G Wang, Y Shen, GB Giannakis IEEE Transactions on Signal Processing 66 (16), 4398-4408, 2018 | 48 | 2018 |
| Ensemble Gaussian processes with spectral features for online interactive learning with scalability Q Lu, G Karanikolas, Y Shen, GB Giannakis International Conference on Artificial Intelligence and Statistics, 1910-1920, 2020 | 46 | 2020 |
| Online Graph-Adaptive Learning With Scalability and Privacy Y Shen, G Leus, GB Giannakis IEEE Transactions on Signal Processing 67 (9), 2471 - 2483, 2019 | 40 | 2019 |
| Heterogeneous online learning for “thing-adaptive” fog computing in IoT T Chen, Q Ling, Y Shen, GB Giannakis IEEE Internet of Things Journal 5 (6), 4328-4341, 2018 | 40 | 2018 |
| Sparse signal recovery from one-bit quantized data: An iterative reweighted algorithm J Fang, Y Shen, H Li, Z Ren Signal Processing 102, 201-206, 2014 | 40 | 2014 |
| Fair node representation learning via adaptive data augmentation OD Kose, Y Shen arXiv preprint arXiv:2201.08549, 2022 | 34 | 2022 |
| Online ensemble multi-kernel learning adaptive to non-stationary and adversarial environments Y Shen, T Chen, G Giannakis International Conference on Artificial Intelligence and Statistics, 2037-2046, 2018 | 34 | 2018 |
| Support knowledge-aided sparse Bayesian learning for compressed sensing J Fang, Y Shen, F Li, H Li, Z Chen 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 34 | 2015 |
| Fairness-aware node representation learning ÖD Köse, Y Shen arXiv preprint arXiv:2106.05391, 2021 | 27 | 2021 |
Georgios B. GiannakisMcKnight Presidential Chair in ECE Dept., University of Minnesota在 umn.edu 的电子邮件经过验证
