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 | 159 | 2022 |
Derivative-free optimization via classification Y Yu, H Qian, YQ Hu Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 101 | 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 | 73 | 2017 |
Derivative-Free Optimization of High-Dimensional Non-Convex Functions by Sequential Random Embeddings. H Qian, YQ Hu, Y Yu IJCAI, 1946-1952, 2016 | 72 | 2016 |
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 | 52 | 2017 |
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 | 47 | 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 | 41 | 2016 |
Derivative-free reinforcement learning: a review H Qian, Y Yu Frontiers of Computer Science 15 (6), 156336, 2021 | 38 | 2021 |
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 | 33 | 2022 |
Zoopt: Toolbox for derivative-free optimization YR Liu, YQ Hu, H Qian, C Qian, Y Yu arXiv preprint arXiv:1801.00329, 2017 | 28 | 2017 |
PS-Tree: A piecewise symbolic regression tree H Zhang, A Zhou, H Qian, H Zhang Swarm and Evolutionary Computation 71, 101061, 2022 | 27 | 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 |
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 | 9 | 2023 |
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 | 9 | 2022 |
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 |
The teaching dimension of regularized kernel learners H Qian, XH Liu, CX Su, A Zhou, Y Yu International Conference on Machine Learning, 17984-18002, 2022 | 4 | 2022 |
Asynchronous classification-based optimization YR Liu, YQ Hu, H Qian, Y Yu Proceedings of the First International Conference on Distributed Artificial …, 2019 | 4 | 2019 |