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cs.LG2026
PerSPL: Personalized Semi-supervised Preference Learning
Xiaoan Xu, Tingzhou Wei, Juncheng Dong +3
Personalized reward models require user-specific preference comparisons, but collecting such feedback is costly and provides only limited supervision for each user. At the same tim…
cs.LG2025
PASTA: A Unified Framework for Offline Assortment Learning
Juncheng Dong, Weibin Mo, Zhengling Qi +3
We study a broad class of assortment optimization problems in an offline and data-driven setting. In such problems, a firm lacks prior knowledge of the underlying choice model, and…