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Found 3 papers, 2 papers with code
Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model
A learning policy may take actions beyond the behavior policy's knowledge, referred to as Out-of-Distribution (OOD) actions.
Diffusion Actor-Critic: Formulating Constrained Policy Iteration as Diffusion Noise Regression for Offline Reinforcement Learning
In this paper, we propose Diffusion Actor-Critic (DAC) that formulates the Kullback-Leibler (KL) constraint policy iteration as a diffusion noise regression problem, enabling direct representation of target policies as diffusion models.
Enhanced Bayesian Personalized Ranking for Robust Hard Negative Sampling in Recommender Systems
In implicit collaborative filtering, hard negative mining techniques are developed to accelerate and enhance the recommendation model learning.
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