Reinforcement Learning with Conformal Action Sets: An Application to Sequential Recommendation
RLCP adapts sequential-recommendation action sets with calibrated pruning, lifting catalog diversity to 1.11–5.21× the best baselines.
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Learning Collective Dynamics with Differentiable Gaussian Representations
Researchers propose Differentiable Gaussian Dynamics to learn population behavior from aggregate counts, beating a DeepAR baseline.