| Stochastic gradient descent for nonconvex learning without bounded gradient assumptions Y Lei, T Hu, G Li, K Tang IEEE transactions on neural networks and learning systems 31 (10), 4394-4400, 2019 | 152 | 2019 |
| Optimization based Layer-wise Magnitude-based Pruning for DNN Compression. G Li, C Qian, C Jiang, X Lu, K Tang IJCAI 330, 2383-2389, 2018 | 84 | 2018 |
| Efficient DNN Neuron Pruning by Minimizing Layer-wise Nonlinear Reconstruction Error. C Jiang, G Li, C Qian, K Tang IJCAI 2018, 2-2, 2018 | 55 | 2018 |
| Reducing idleness in financial cloud services via multi-objective evolutionary reinforcement learning based load balancer P Yang, L Zhang, H Liu, G Li Science China Information Sciences 67 (2), 120102, 2024 | 40 | 2024 |
| Distributed Pareto Optimization for Subset Selection. C Qian, G Li, C Feng, K Tang IJCAI, 1492-1498, 2018 | 19 | 2018 |
| Stage-wise magnitude-based pruning for recurrent neural networks G Li, P Yang, C Qian, R Hong, K Tang IEEE Transactions on Neural Networks and Learning Systems 35 (2), 1666-1680, 2022 | 18 | 2022 |
| Multi‐objective evolutionary optimization for hardware‐aware neural network pruning W Hong, G Li, S Liu, P Yang, K Tang Fundamental Research 4 (4), 941-950, 2024 | 12 | 2024 |
| Learning to solve capacitated arc routing problems by policy gradient H Li, G Li 2019 IEEE Congress on Evolutionary Computation (CEC), 1291-1298, 2019 | 11 | 2019 |
| Relief R-CNN: Utilizing convolutional features for fast object detection G Li, J Liu, C Jiang, L Zhang, M Lin, K Tang International Symposium on Neural Networks, 386-394, 2017 | 6 | 2017 |
| Accelerate proposal generation in R-CNN methods for fast pedestrian extraction J Wang, G Li The Electronic Library 37 (3), 435-453, 2019 | 4 | 2019 |
| Relief impression image detection: Unsupervised extracting objects directly from feature arrangements of deep cnn G Li, J Liu, C Jiang, K Tang arXiv preprint arXiv:1601.06719, 2016 | 4 | 2016 |
| Ocet: One-dimensional convolution embedding transformer for stock trend prediction P Yang, L Fu, J Zhang, G Li International Conference on Bio-Inspired Computing: Theories and …, 2022 | 3 | 2022 |
| Reinforcement learning based vertical scaling for hybrid deployment in cloud computing J Cao, G Li, P Yang International Conference on Bio-Inspired Computing: Theories and …, 2022 | 1 | 2022 |
| Relief r-cnn: Utilizing convolutional feature interrelationship for fast object detection deployment G Li, J Liu, C Jiang, L Zhang, K Tang, Z Zhu arXiv preprint arXiv:1601.06719, 2016 | 1 | 2016 |
| Hardware-Aware DNN Compression for Homogeneous Edge Devices K Zhang, G Li, N Lu, P Yang, K Tang arXiv preprint arXiv:2501.15240, 2025 | | 2025 |
| Causal Inference Based Large-Scale Multi-Objective Optimization B Li, Y Yang, P Yang, G Li, K Tang, A Zhou IEEE Transactions on Evolutionary Computation, 2025 | | 2025 |
| Noise-Tolerant Hardware-Aware Pruning for Deep Neural Networks S Lu, C Chen, K Zhang, Y Zheng, Z Hu, W Hong, G Li, X Yao International Conference on Swarm Intelligence, 127-138, 2023 | | 2023 |
| Method, system, server, and storage medium for logistics management based on QR code G Li, P Yang, K Tang, X Yao US Patent 11,631,261, 2023 | | 2023 |
| Enabling surrogate-assisted evolutionary reinforcement learning via policy embedding L Tang, X Li, J Zhang, G Li, P Yang, K Tang International Conference on Bio-Inspired Computing: Theories and …, 2022 | | 2022 |
| Dynamic and Adaptive Threshold for DNN Compression from Scratch C Jiang, G Li, C Qian Simulated Evolution and Learning: 11th International Conference, SEAL 2017 …, 2017 | | 2017 |
Ke TangProfessor, Southern University of Science and TechnologyVerified email at sustech.edu.cn