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cs.LG2025
Learning Network Dismantling Without Handcrafted Inputs
Haozhe Tian, Pietro Ferraro, Robert Shorten +2
The application of message-passing Graph Neural Networks has been a breakthrough for important network science problems. However, the competitive performance often relies on using…
cs.LG2024
Reinforcement Learning with Adaptive Regularization for Safe Control of Critical Systems
Haozhe Tian, Homayoun Hamedmoghadam, Robert Shorten +1
Reinforcement Learning (RL) is a powerful method for controlling dynamic systems, but its learning mechanism can lead to unpredictable actions that undermine the safety of critical…