3 citations · 7 across the 6 of their papers we have counts for
6 papers
Towards Generalized Inverse Reinforcement Learning
Chaosheng Dong, Yijia Wang
This paper studies generalized inverse reinforcement learning (GIRL) in Markov decision processes (MDPs), that is, the problem of learning the basic components of an MDP given obse…
Faster Reinforcement Learning by Freezing Slow States
Yijia Wang, Daniel R. Jiang
We study infinite horizon Markov decision processes (MDPs) with "fast-slow" structure, where some state variables evolve rapidly ("fast states") while others change more gradually…
One Backward from Ten Forward, Subsampling for Large-Scale Deep Learning
Chaosheng Dong, Xiaojie Jin, Weihao Gao +5
Deep learning models in large-scale machine learning systems are often continuously trained with enormous data from production environments. The sheer volume of streaming training…
Inverse Multiobjective Optimization Through Online Learning
Chaosheng Dong, Yijia Wang, Bo Zeng
We study the problem of learning the objective functions or constraints of a multiobjective decision making model, based on a set of sequentially arrived decisions. In particular,…
Dynamic Subgoal-based Exploration via Bayesian Optimization
Yijia Wang, Matthias Poloczek, Daniel R. Jiang
Reinforcement learning in sparse-reward navigation environments with expensive and limited interactions is challenging and poses a need for effective exploration. Motivated by comp…
Structured Actor-Critic for Managing Public Health Points-of-Dispensing
Yijia Wang, Daniel R. Jiang
Public health organizations face the problem of dispensing treatments (i.e., vaccines, antibiotics, and others) to groups of affected populations through "points-of-dispensing" (PO…