11 citations · 26 across the 12 of their papers we have counts for
5 papers · 1 filter
Residual-Quantile Adjustment for Adaptive Training of Physics-informed Neural Network
Jiayue Han, Zhiqiang Cai, Zhiyou Wu +1
Adaptive training methods for Physics-informed neural network (PINN) require dedicated constructions of the distribution of weights assigned at each training sample. To efficiently…
Learn Quasi-stationary Distributions of Finite State Markov Chain
Zhiqiang Cai, Ling Lin, Xiang Zhou
We propose a reinforcement learning (RL) approach to compute the expression of quasi-stationary distribution. Based on the fixed-point formulation of quasi-stationary distribution,…
Sublinear Regret for Learning POMDPs
Yi Xiong, Ningyuan Chen, Xuefeng Gao +1
We study the model-based undiscounted reinforcement learning for partially observable Markov decision processes (POMDPs). The oracle we consider is the optimal policy of the POMDP…
Machine Learning and Control Theory
Alain Bensoussan, Yiqun Li, Dinh Phan Cao Nguyen +3
We survey in this article the connections between Machine Learning and Control Theory. Control Theory provide useful concepts and tools for Machine Learning. Conversely Machine Lea…
Regime Switching Bandits
Xiang Zhou, Yi Xiong, Ningyuan Chen +1
We study a multi-armed bandit problem where the rewards exhibit regime switching. Specifically, the distributions of the random rewards generated from all arms are modulated by a c…