#policy learning
6 papers match
Multi-channel Uplift Policy Learning
Changjian Liu, Tianyu Wang, Xiaoxuan Deng +7
The paper proposes ReAlloc, a causal teacher‑student framework for allocating fixed marketing budgets across multiple e‑commerce channels, using unbiased local gradients and long‑t…
SCOPE: Supply-Chain Operations through Coupled Policies for End-to-End Coordination
Yunhao Liang, Xianqi Cao, Pujun Zhang +4
The paper introduces SCOPE, a unified policy framework that jointly optimizes assortment, source assignment, replenishment frequency, and routing decisions in supply chains, showin…
DLAM: Distributional Latent Actions with Temporal Constraints
Zuojin Tang, Feifan Luo, Haoyun Liu +10
The paper introduces DLAM, a distributional latent-action model that encodes video transitions as diagonal Gaussians with temporal constraints, improving reconstruction consistency…
Learning Who to Treat When Treatment is Missing
Johnna Sundberg, Rayid Ghani, Eli Ben-Michael +1
The paper develops efficient estimators for policy learning when treatment assignments are missing, handling both missing-at-random and missing-completely-conditionally-at-random s…
ChunkFlow: Towards Continuity-Consistent Chunked Policy Learning
Zhao Yang, Yinan Shi, Mingyuan Yao +3
ChunkFlow introduces a seam‑aware training and execution framework for chunked robot policies that reduces boundary jitter by using deterministic overlap blending and continuity lo…
EDAR: Learning Environment-Dependent Action Representations for Robotic Manipulation
Yuecheng Xu, Tong Yang, Jingkai Jia +3
The paper introduces EDAR, a method that learns action representations for robotic manipulation by linking control commands with the visual effects they cause in a given environmen…