2025 | Zeyuan Ma et. al. “Surrogate Learning in Meta-Black-Box Optimization: A Preliminary Study” The Genetic and Evolutionary Computation Conference (2025) |
2025 | Zeyuan Ma et. al. “Accurate Peak Detection in Multimodal Optimization via Approximated Landscape Learning” The Genetic and Evolutionary Computation Conference (2025) |
2025 | Hongshu Guo et. al. “Reinforcement Learning-based Self-adaptive Differential Evolution through Automated Landscape Feature Learning” The Genetic and Evolutionary Computation Conference (2025) |
2025 | Hongshu Guo*, Zeyuan Ma*, Jiacheng Chen, et. al. “ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning” (AAAI 2025, Oral). |
2024 | Zeyuan Ma*, Jiacheng Chen*, Hongshu Guo, et. al. “Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization” ICLR (2025). |
2024 | Zeyuan Ma*, Jiacheng Chen*, Hongshu Guo, et. al. “Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning” The Genetic and Evolutionary Computation Conference (2024). |
2024 | Hongqiao Lian, Zeyuan Ma, Hongshu Guo, et. al. “RLEMMO: Evolutionary Multimodal Optimization Assisted By Deep Reinforcement Learning” The Genetic and Evolutionary Computation Conference (2024). |
2024 | Hongshu Guo, Zeyuan Ma, Jiacheng Chen, et. al. “Deep Reinforcement Learning for Dynamic Algorithm Selection: A Proof-of-Principle Study on Differential Evolution” IEEE Transactions on Systems, Man, and Cybernetics: Systems (2024). |
2024 | Jiacheng Chen*, Zeyuan Ma*, et. al. “Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning” The Twelfth International Conference on Learning Representations (ICLR 2024) |