| Fast greedy map inference for determinantal point process to improve recommendation diversity L Chen, G Zhang, H Zhou Proceedings of the 32nd International Conference on Neural Information …, 2018 | 381 | 2018 |
| 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 |
| Perturbation analysis of orthogonal matching pursuit J Ding, L Chen, Y Gu IEEE Transactions on Signal processing 61 (2), 398-410, 2012 | 87 | 2012 |
| Square-root lasso with nonconvex regularization: An admm approach X Shen, L Chen, Y Gu, HC So IEEE Signal Processing Letters 23 (7), 934-938, 2016 | 44 | 2016 |
| Improving the diversity of top-N recommendation via determinantal point process L Chen, G Zhang, H Zhou Large Scale Recommendation Systems Workshop, 2017 | 33 | 2017 |
| On the theoretical analysis of cross validation in compressive sensing J Zhang, L Chen, PT Boufounos, Y Gu 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 30 | 2014 |
| On the performance bound of sparse estimation with sensing matrix perturbation Y Tang, L Chen, Y Gu IEEE transactions on signal processing 61 (17), 4372-4386, 2013 | 30 | 2013 |
| A calibration system and perturbation analysis for the Modulated Wideband Converter L Chen, J Jin, Y Gu IEEE 10th International Conference on Signal Processing Proceedings, 78-81, 2010 | 26 | 2010 |
| Proof of convergence and performance analysis for sparse recovery via zero-point attracting projection X Wang, Y Gu, L Chen IEEE transactions on signal processing 60 (8), 4081-4093, 2012 | 19 | 2012 |
| Interformer: Towards effective heterogeneous interaction learning for click-through rate prediction Z Zeng, X Liu, M Hang, X Liu, Q Zhou, C Yang, Y Liu, Y Ruan, L Chen, ... arXiv preprint arXiv:2411.09852, 2024 | 18 | 2024 |
| External large foundation model: How to efficiently serve trillions of parameters for online ads recommendation M Liang, X Liu, R Jin, B Liu, Q Suo, Q Zhou, S Zhou, L Chen, H Zheng, ... Companion Proceedings of the ACM on Web Conference 2025, 344-353, 2025 | 14 | 2025 |
| The convergence guarantees of a non-convex approach for sparse recovery using regularized least squares L Chen, Y Gu 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 14 | 2014 |
| Robustness of orthogonal matching pursuit for multiple measurement vectors in noisy scenario J Ding, L Chen, Y Gu 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 14 | 2012 |
| On the Null Space Constant forMinimization L Chen, Y Gu IEEE Signal Processing Letters 22 (10), 1600-1603, 2015 | 13 | 2015 |
| Hulu video recommendation: from relevance to reasoning X Xu, L Chen, S Zu, H Zhou Proceedings of the 12th ACM Conference on Recommender Systems, 482-482, 2018 | 11 | 2018 |
| Local and global optimality of LP minimization for sparse recovery L Chen, Y Gu 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 11 | 2015 |
| Performance of orthogonal matching pursuit for multiple measurement vectors J Ding, L Chen, Y Gu arXiv preprint arXiv:1109.6390, 2011 | 11 | 2011 |
| Oracle-order recovery performance of greedy pursuits with replacement against general perturbations L Chen, Y Gu IEEE transactions on signal processing 61 (18), 4625-4636, 2013 | 10 | 2013 |
| Fast sparse recovery via non-convex optimization L Chen, Y Gu 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2015 | 9 | 2015 |
| Cross validation in compressive sensing and its application of OMP-CV algorithm J Zhang, L Chen, PT Boufounos, Y Gu arXiv preprint arXiv:1602.06373, 2016 | 8 | 2016 |
Yuantao GuDepartment of Electronic Engineering, Tsinghua UniversityVerified email at tsinghua.edu.cn
