5 papers · 1 filter
Sobolev Regularized Score Difference Estimation in Diffusion Models
Chenghan Xie, Jose Blanchet, Renyuan Xu
Estimating the difference of two Stein's score functions is a fundamental problem in generative modeling. In particular, score differences arise naturally in transfer learning, whe…
Robust Assortment Optimization from Observational Data
Miao Lu, Yuxuan Han, Han Zhong +2
Assortment optimization is a fundamental challenge in modern retail and recommendation systems, where the goal is to select a subset of products that maximizes expected revenue und…
Learning an Optimal Assortment Policy under Observational Data
Yuxuan Han, Han Zhong, Miao Lu +2
We study the fundamental problem of offline assortment optimization under the Multinomial Logit (MNL) model, where sellers must determine the optimal subset of the products to offe…
ScoreFusion: Fusing Score-based Generative Models via Kullback-Leibler Barycenters
Hao Liu, Junze Tony Ye, Jose Blanchet +1
We introduce ScoreFusion, a theoretically grounded method for fusing multiple pre-trained diffusion models that are assumed to generate from auxiliary populations. ScoreFusion is p…
Learning Optimal Distributionally Robust Stochastic Control in Continuous State Spaces
Shengbo Wang, Jason Meng, Nian Si +2
We study data-driven learning of robust stochastic control for infinite-horizon systems with potentially continuous state and action spaces. In many managerial settings--supply cha…