60 citations · 188 across the 25 of their papers we have counts for
10 papers · 1 filter
Nonparametric Additive Value Functions: Interpretable Reinforcement Learning with an Application to Surgical Recovery
Patrick Emedom-Nnamdi, Timothy R. Smith, Jukka-Pekka Onnela +1
We propose a nonparametric additive model for estimating interpretable value functions in reinforcement learning, with an application in optimizing postoperative recovery through p…
Combinatorial Inference on the Optimal Assortment in Multinomial Logit Models
Shuting Shen, Xi Chen, Ethan X. Fang +1
Assortment optimization has received active explorations in the past few decades due to its practical importance. Despite the extensive literature dealing with optimization algorit…
Federated Offline Reinforcement Learning
Doudou Zhou, Yufeng Zhang, Aaron Sonabend-W +3
Evidence-based or data-driven dynamic treatment regimes are essential for personalized medicine, which can benefit from offline reinforcement learning (RL). Although massive health…
Lagrangian Inference for Ranking Problems
Yue Liu, Ethan X. Fang, Junwei Lu
We propose a novel combinatorial inference framework to conduct general uncertainty quantification in ranking problems. We consider the widely adopted Bradley-Terry-Luce (BTL) mode…
Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices
Doudou Zhou, Tianxi Cai, Junwei Lu
Matrix completion has attracted attention in many fields, including statistics, applied mathematics, and electrical engineering. Most of the works focus on the independent sampling…
Estimating and Inferring the Maximum Degree of Stimulus-Locked Time-Varying Brain Connectivity Networks
Kean Ming Tan, Junwei Lu, Tong Zhang +1
Neuroscientists have enjoyed much success in understanding brain functions by constructing brain connectivity networks using data collected under highly controlled experimental set…