A diversity-enhanced subset selection framework for multimodal multiobjective optimization Y Peng, H Ishibuchi IEEE Transactions on Evolutionary Computation 26 (5), 886-900, 2021 | 26 | 2021 |
An adaptive clipping approach for proximal policy optimization G Chen, Y Peng, M Zhang arXiv preprint arXiv:1804.06461, 2018 | 24 | 2018 |
NEAT for large-scale reinforcement learning through evolutionary feature learning and policy gradient search Y Peng, G Chen, H Singh, M Zhang Proceedings of the Genetic and Evolutionary Computation Conference, 490-497, 2018 | 15 | 2018 |
Effective exploration for deep reinforcement learning via bootstrapped q-ensembles under tsallis entropy regularization G Chen, Y Peng, M Zhang arXiv preprint arXiv:1809.00403, 2018 | 11 | 2018 |
Off-policy actor-critic in an ensemble: Achieving maximum general entropy and effective environment exploration in deep reinforcement learning G Chen, Y Peng arXiv preprint arXiv:1902.05551, 2019 | 8 | 2019 |
A federated network online network traffics analysis engine for cybersecurity S Pang, Y Peng, T Ban, D Inoue, A Sarrafzadeh 2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015 | 7 | 2015 |
Chunk incremental idr/qr lda learning Y Peng, S Pang, G Chen, A Sarrafzadeh, T Ban, D Inoue The 2013 International Joint Conference on Neural Networks (IJCNN), 1-8, 2013 | 6 | 2013 |
Effective policy gradient search for reinforcement learning through NEAT based feature extraction Y Peng, G Chen, M Zhang, Y Mei Simulated Evolution and Learning: 11th International Conference, SEAL 2017 …, 2017 | 5 | 2017 |
Multi-modal multi-objective test problems with an infinite number of equivalent pareto sets H Ishibuchi, Y Peng, LM Pang 2022 IEEE congress on evolutionary computation (CEC), 1-8, 2022 | 4 | 2022 |
A sandpile model for reliable actor-critic reinforcement learning Y Peng, G Chen, M Zhang, S Pang 2017 International Joint Conference on Neural Networks (IJCNN), 4014-4021, 2017 | 4 | 2017 |
Environmental selection using a fuzzy classifier for multiobjective evolutionary algorithms J Zhang, H Ishibuchi, K Shang, L He, LM Pang, Y Peng Proceedings of the Genetic and Evolutionary Computation Conference, 485-492, 2021 | 3 | 2021 |
Evolving transferable artificial neural networks for gameplay tasks via NEAT with phased searching W Hardwick-Smith, Y Peng, G Chen, Y Mei, M Zhang AI 2017: Advances in Artificial Intelligence: 30th Australasian Joint …, 2017 | 3 | 2017 |
A Decomposition-based Hybrid Evolutionary Algorithm for Multi-modal Multi-objective Optimization Y Peng, H Ishibuchi 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2021 | 2 | 2021 |
Niching diversity estimation for multi-modal multi-objective optimization Y Peng, H Ishibuchi Evolutionary Multi-Criterion Optimization: 11th International Conference …, 2021 | 2 | 2021 |
Constrained expectation-maximization methods for effective reinforcement learning G Chen, Y Peng, M Zhang 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 2 | 2018 |
Generalized compatible function approximation for policy gradient search Y Peng, G Chen, M Zhang, S Pang Neural Information Processing: 23rd International Conference, ICONIP 2016 …, 2016 | 2 | 2016 |
Exploring crude oil impacts to oil stocks through graphical computational correlation analysis A Lai, L Song, Y Peng, P Zhang, Q Wang, S Pang Neural Information Processing: 19th International Conference, ICONIP 2012 …, 2012 | 2 | 2012 |
Effective Linear Policy Gradient Search through Primal-Dual Approximation Y Peng, G Chen, M Zhang 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 1 | 2020 |
Policy Direct Search for Effective Reinforcement Learning Y Peng Open Access Te Herenga Waka-Victoria University of Wellington, 2019 | 1 | 2019 |
Boosting performance of incremental IDR/QR LDA-from sequential to chunk Y Peng Auckland University of Technology, 2011 | 1 | 2011 |