| Sparse LMS for system identification Y Chen, Y Gu, AO Hero 2009 IEEE international conference on acoustics, speech and signal …, 2009 | 928 | 2009 |
| L0 Norm Constraint LMS for Sparse System Identification Y Gu, J Jin, S Mei Signal Processing Letters, IEEE 16 (9), 774-777, 2009 | 652* | 2009 |
| Minimum error entropy Kalman filter B Chen, L Dang, Y Gu, N Zheng, JC Príncipe IEEE Transactions on Systems, Man, and Cybernetics: Systems 51 (9), 5819-5829, 2019 | 263 | 2019 |
| Performance analysis of L0 norm constraint least mean square algorithm G Su, J Jin, Y Gu, J Wang IEEE Transactions on Signal Processing 60 (5), 2223-2235, 2012 | 218 | 2012 |
| Disciplined convex-concave programming X Shen, S Diamond, Y Gu, S Boyd 2016 IEEE 55th conference on decision and control (CDC), 1009-1014, 2016 | 212 | 2016 |
| A stochastic gradient approach on compressive sensing signal reconstruction based on adaptive filtering framework J Jin, Y Gu, S Mei IEEE Journal of Selected Topics in Signal Processing 4 (2), 409-420, 2010 | 208 | 2010 |
| Local-set-based graph signal reconstruction X Wang, P Liu, Y Gu IEEE transactions on signal processing 63 (9), 2432-2444, 2015 | 196 | 2015 |
| Time-varying graph signal reconstruction K Qiu, X Mao, X Shen, X Wang, T Li, Y Gu IEEE Journal of Selected Topics in Signal Processing 11 (6), 870-883, 2017 | 182 | 2017 |
| Breaking the sample size barrier in model-based reinforcement learning with a generative model G Li, Y Wei, Y Chi, Y Gu, Y Chen Advances in neural information processing systems 33, 12861-12872, 2020 | 169 | 2020 |
| Linearized ADMM for nonconvex nonsmooth optimization with convergence analysis Q Liu, X Shen, Y Gu IEEE access 7, 76131-76144, 2019 | 162 | 2019 |
| Is Q-learning minimax optimal? a tight sample complexity analysis G Li, C Cai, Y Chen, Y Wei, Y Chi Operations Research 72 (1), 222-236, 2024 | 140 | 2024 |
| LMS algorithm with gradient descent filter length Y Gu, K Tang, H Cui IEEE Signal Processing Letters 11 (3), 305-307, 2004 | 138 | 2004 |
| Sample complexity of asynchronous Q-learning: Sharper analysis and variance reduction G Li, Y Wei, Y Chi, Y Gu, Y Chen Advances in neural information processing systems 33, 7031-7043, 2020 | 119 | 2020 |
| The convergence guarantees of a non-convex approach for sparse recovery L Chen, Y Gu IEEE Transactions on Signal Processing 62 (15), 3754-3767, 2014 | 110 | 2014 |
| Regularized least-mean-square algorithms Y Chen, Y Gu, AO Hero arXiv preprint arXiv:1012.5066, 2010 | 100 | 2010 |
| Convergence analysis of a deficient-length LMS filter and optimal-length sequence to model exponential decay impulse response Y Gu, K Tang, H Cui, W Du IEEE Signal Processing Letters 10 (1), 4-7, 2003 | 96 | 2003 |
| Walkman: A communication-efficient random-walk algorithm for decentralized optimization X Mao, K Yuan, Y Hu, Y Gu, AH Sayed, W Yin IEEE Transactions on Signal Processing 68, 2513-2528, 2020 | 95 | 2020 |
| SageFormer: Series-aware framework for long-term multivariate time-series forecasting Z Zhang, L Meng, Y Gu IEEE Internet of Things Journal 11 (10), 18435-18448, 2024 | 90 | 2024 |
| Block-sparsity-induced adaptive filter for multi-clustering system identification S Jiang, Y Gu IEEE Transactions on Signal Processing 63 (20), 5318-5330, 2015 | 90 | 2015 |
| Perturbation analysis of orthogonal matching pursuit J Ding, L Chen, Y Gu IEEE Transactions on Signal processing 61 (2), 398-410, 2012 | 87 | 2012 |
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