| Subset selection by Pareto optimization C Qian, Y Yu, ZH Zhou Advances in neural information processing systems 28, 2015 | 233 | 2015 |
| Evolutionary learning: Advances in theories and algorithms ZH Zhou, Y Yu, C Qian Springer, 2019 | 206 | 2019 |
| An analysis on recombination in multi-objective evolutionary optimization C Qian, Y Yu, ZH Zhou Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011 | 137 | 2011 |
| Pareto ensemble pruning C Qian, Y Yu, ZH Zhou Proceedings of the AAAI conference on artificial intelligence 29 (1), 2015 | 132 | 2015 |
| Reducing the uncertainty in estimating soil microbial-derived carbon storage H Hu, C Qian, K Xue, RG Jörgensen, M Keiluweit, C Liang, X Zhu, J Chen, ... Proceedings of the National Academy of Sciences 121 (35), e2401916121, 2024 | 99 | 2024 |
| Subset selection under noise C Qian, JC Shi, Y Yu, K Tang, ZH Zhou Advances in neural information processing systems 30, 2017 | 98 | 2017 |
| 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 | 95 | 2018 |
| On Subset Selection with General Cost Constraints. C Qian, JC Shi, Y Yu, K Tang IJCAI 17, 2613-2619, 2017 | 82 | 2017 |
| On the effectiveness of sampling for evolutionary optimization in noisy environments C Qian, Y Yu, K Tang, Y Jin, X Yao, ZH Zhou Evolutionary computation 26 (2), 237-267, 2018 | 80* | 2018 |
| Constrained Monotone -Submodular Function Maximization Using Multiobjective Evolutionary Algorithms With Theoretical Guarantee C Qian, JC Shi, K Tang, ZH Zhou IEEE Transactions on Evolutionary Computation 22 (4), 595-608, 2017 | 79 | 2017 |
| Better running time of the non-dominated sorting genetic algorithm II (NSGA-II) by using stochastic tournament selection C Bian, C Qian International Conference on Parallel Problem Solving from Nature, 428-441, 2022 | 75* | 2022 |
| Stochastic population update can provably be helpful in multi-objective evolutionary algorithms C Bian, Y Zhou, M Li, C Qian Artificial Intelligence 341, 104308, 2025 | 70 | 2025 |
| Multi-agent dynamic algorithm configuration K Xue, J Xu, L Yuan, M Li, C Qian, Z Zhang, Y Yu Advances in Neural Information Processing Systems 35, 20147-20161, 2022 | 69 | 2022 |
| Maximizing submodular or monotone approximately submodular functions by multi-objective evolutionary algorithms C Qian, Y Yu, K Tang, X Yao, ZH Zhou Artificial Intelligence 275, 279-294, 2019 | 69 | 2019 |
| Towards generalizable neural solvers for vehicle routing problems via ensemble with transferrable local policy C Gao, H Shang, K Xue, D Li, C Qian arXiv preprint arXiv:2308.14104, 2023 | 67 | 2023 |
| Selection hyper-heuristics can provably be helpful in evolutionary multi-objective optimization C Qian, K Tang, ZH Zhou International conference on parallel problem solving from nature, 835-846, 2016 | 65 | 2016 |
| Analyzing evolutionary optimization in noisy environments C Qian, Y Yu, ZH Zhou Evolutionary computation 26 (1), 1-41, 2018 | 62 | 2018 |
| Parallel Pareto Optimization for Subset Selection. C Qian, JC Shi, Y Yu, K Tang, ZH Zhou IJCAI, 1939-1945, 2016 | 62 | 2016 |
| Monte carlo tree search based variable selection for high dimensional bayesian optimization L Song, K Xue, X Huang, C Qian Advances in Neural Information Processing Systems 35, 28488-28501, 2022 | 61 | 2022 |
| Efficient DNN Neuron Pruning by Minimizing Layer-wise Nonlinear Reconstruction Error. C Jiang, G Li, C Qian, K Tang IJCAI 2018, 2-2, 2018 | 59 | 2018 |
