2 citations · 4 across the 13 of their papers we have counts for
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cs.LG2025
Enhancing Adversarial Transferability through Block Stretch and Shrink
Quan Liu, Feng Ye, Chenhao Lu +4
Input transformation-based attacks improve adversarial transferability by aggregating gradients over transformed inputs. Existing analyses mainly explain their efficacy from image…
cs.LG2024★ 1 cited
Rethinking Transformers in Solving POMDPs
Chenhao Lu, Ruizhe Shi, Yuyao Liu +3
Sequential decision-making algorithms such as reinforcement learning (RL) in real-world scenarios inevitably face environments with partial observability. This paper scrutinizes th…
cs.LG2023★ 2 cited
Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization
Kun Lei, Zhengmao He, Chenhao Lu +3
Combining offline and online reinforcement learning (RL) is crucial for efficient and safe learning. However, previous approaches treat offline and online learning as separate proc…