| Meta-SAGE: scale meta-learning scheduled adaptation with guided exploration for mitigating scale shift on combinatorial optimization J Son, M Kim, H Kim, J Park International Conference on Machine Learning, 32194-32210, 2023 | 10* | 2023 |
| RL4CO: a Unified Reinforcement Learning for Combinatorial Optimization Library F Berto, C Hua, J Park, M Kim, H Kim, J Son, H Kim, J Kim, J Park NeurIPS 2023 Workshop: New Frontiers in Graph Learning, 2023 | 7* | 2023 |
| To be biased or not to be: Choosing between design fixation and design intentionality J Kim, H Ryu, H Kim CHI'13 Extended Abstracts on Human Factors in Computing Systems, 349-354, 2013 | 4 | 2013 |
| Scale-conditioned adaptation for large scale combinatorial optimization M Kim, J Son, H Kim, J Park NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022 | 3 | 2022 |
| A Neural Separation Algorithm for the Rounded Capacity Inequalities H Kim, J Park, C Kwon INFORMS Journal on Computing, 2024 | 1 | 2024 |
| Enhancing Sample Efficiency in Black-box Combinatorial Optimization via Symmetric Replay Training H Kim, M Kim, S Ahn, J Park | 1* | 2023 |
| Neural Coarsening Process for Multi-level Graph Combinatorial Optimization H Kim, M Kim, C Kwon, J Park NeurIPS 2022 Workshop: New Frontiers in Graph Learning, 2022 | 1 | 2022 |
| Equity-Transformer: Solving NP-Hard Min-Max Routing Problems as Sequential Generation with Equity Context J Son, M Kim, S Choi, H Kim, J Park Proceedings of the AAAI Conference on Artificial Intelligence 38 (18), 20265 …, 2024 | | 2024 |
| Ant Colony Sampling with GFlowNets for Combinatorial Optimization M Kim, S Choi, J Son, H Kim, J Park, Y Bengio arXiv preprint arXiv:2403.07041, 2024 | | 2024 |
| Genetic-guided GFlowNets: Advancing in Practical Molecular Optimization Benchmark H Kim, M Kim, S Choi, J Park arXiv preprint arXiv:2402.05961, 2024 | | 2024 |
Jinkyoo ParkDepartment of Industrial and Systems Engineering, KAISTVerified email at kaist.ac.kr
