49 citations · 71 across the 13 of their papers we have counts for
Showing 2022Show all
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cs.LG2022★ 2 cited
State Advantage Weighting for Offline RL
Jiafei Lyu, Aicheng Gong, Le Wan +2
We present state advantage weighting for offline reinforcement learning (RL). In contrast to action advantage that we commonly adopt in QSA learning, we leverage state adv…
cs.IR2022★ 1 cited
Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation
Chang Meng, Ziqi Zhao, Wei Guo +6
Multi-types of behaviors (e.g., clicking, adding to cart, purchasing, etc.) widely exist in most real-world recommendation scenarios, which are beneficial to learn users' multi-fac…
cs.LG2022★ 11 cited
Double Check Your State Before Trusting It: Confidence-Aware Bidirectional Offline Model-Based Imagination
Jiafei Lyu, Xiu Li, Zongqing Lu
The learned policy of model-free offline reinforcement learning (RL) methods is often constrained to stay within the support of datasets to avoid possible dangerous out-of-distribu…