| Black-box tuning for language-model-as-a-service T Sun, Y Shao, H Qian, X Huang, X Qiu International Conference on Machine Learning, 20841-20855, 2022 | 190 | 2022 |
| Derivative-free optimization via classification Y Yu, H Qian, YQ Hu Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 105 | 2016 |
| Solving high-dimensional multi-objective optimization problems with low effective dimensions H Qian, Y Yu Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 75 | 2017 |
| Derivative-Free Optimization of High-Dimensional Non-Convex Functions by Sequential Random Embeddings. H Qian, YQ Hu, Y Yu IJCAI, 1946-1952, 2016 | 73 | 2016 |
| BBTv2: Towards a gradient-free future with large language models T Sun, Z He, H Qian, Y Zhou, X Huang, X Qiu arXiv preprint arXiv:2205.11200, 2022 | 58 | 2022 |
| Sequential classification-based optimization for direct policy search YQ Hu, H Qian, Y Yu Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 55 | 2017 |
| Expensive multiobjective optimization by relation learning and prediction H Hao, A Zhou, H Qian, H Zhang IEEE Transactions on Evolutionary Computation 26 (5), 1157-1170, 2022 | 45 | 2022 |
| Symbolic execution of complex program driven by machine learning based constraint solving X Li, Y Liang, H Qian, YQ Hu, L Bu, Y Yu, X Chen, X Li Proceedings of the 31st IEEE/ACM International Conference on Automated …, 2016 | 42 | 2016 |
| Derivative-free reinforcement learning: A review H Qian, Y Yu Frontiers of Computer Science 15 (6), 156336, 2021 | 39 | 2021 |
| Zoopt: Toolbox for derivative-free optimization YR Liu, YQ Hu, H Qian, C Qian, Y Yu arXiv preprint arXiv:1801.00329, 2017 | 30 | 2017 |
| PS-Tree: A piecewise symbolic regression tree H Zhang, A Zhou, H Qian, H Zhang Swarm and Evolutionary Computation 71, 101061, 2022 | 29 | 2022 |
| Scaling simultaneous optimistic optimization for high-dimensional non-convex functions with low effective dimensions H Qian, Y Yu Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 24 | 2016 |
| The sampling-and-learning framework: A statistical view of evolutionary algorithms Y Yu, H Qian 2014 IEEE Congress on Evolutionary Computation (CEC), 149-158, 2014 | 14 | 2014 |
| Bbtv2: Pure black-box optimization can be comparable to gradient descent for few-shot learning T Sun, Z He, H Qian, X Huang, X Qiu arXiv preprint arXiv:2205.11200, 2022 | 12 | 2022 |
| Noisy derivative-free optimization with value suppression H Wang, H Qian, Y Yu Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 11 | 2018 |
| On the opportunities of green computing: A survey Y Zhou, X Lin, X Zhang, M Wang, G Jiang, H Lu, Y Wu, K Zhang, Z Yang, ... arXiv preprint arXiv:2311.00447, 2023 | 10 | 2023 |
| On sampling-and-classification optimization in discrete domains H Qian, Y Yu 2016 IEEE Congress on Evolutionary Computation (CEC), 4374-4381, 2016 | 9 | 2016 |
| Machine learning steered symbolic execution framework for complex software code L Bu, Y Liang, Z Xie, H Qian, YQ Hu, Y Yu, X Chen, X Li Formal Aspects of Computing 33 (3), 301-323, 2021 | 6 | 2021 |
| A Comprehensive Exploration of Personalized Learning in Smart Education: From Student Modeling to Personalized Recommendations S Wu, Y Cao, J Cui, R Li, H Qian, B Jiang, W Zhang arXiv preprint arXiv:2402.01666, 2024 | 5 | 2024 |
| Asynchronous classification-based optimization YR Liu, YQ Hu, H Qian, Y Yu Proceedings of the First International Conference on Distributed Artificial …, 2019 | 5 | 2019 |
Yang YuProfessor, Nanjing UniversityVerified email at nju.edu.cn
