2 citations · 2 across the 6 of their papers we have counts for
12 papers
Stochastic Gradient Descent with Dependent Data for Offline Reinforcement Learning
Jing Dong, Xin T. Tong
In reinforcement learning (RL), offline learning decoupled learning from data collection and is useful in dealing with exploration-exploitation tradeoff and enables data reuse in m…
Exploration Enhancement of Nature-Inspired Swarm-based Optimization Algorithms
Kwok Pui Choi, Enzio Hai Hong Kam, Tze Leung Lai +2
Nature-inspired swarm-based algorithms have been widely applied to tackle high-dimensional and complex optimization problems across many disciplines. They are general purpose optim…
Spectral Gap of Replica Exchange Langevin Diffusion on Mixture Distributions
Jing Dong, Xin T. Tong
Langevin diffusion (LD) is one of the main workhorses for sampling problems. However, its convergence rate can be significantly reduced if the target distribution is a mixture of m…
Consistency analysis of bilevel data-driven learning in inverse problems
Neil K. Chada, Claudia Schillings, Xin T. Tong +1
One fundamental problem when solving inverse problems is how to find regularization parameters. This article considers solving this problem using data-driven bilevel optimization,…
Dimension Independent Generalization Error by Stochastic Gradient Descent
Xi Chen, Qiang Liu, Xin T. Tong
One classical canon of statistics is that large models are prone to overfitting, and model selection procedures are necessary for high dimensional data. However, many overparameter…
Analysis of a localised nonlinear Ensemble Kalman Bucy Filter with complete and accurate observations
Jana de Wiljes, Xin T. Tong
Concurrent observation technologies have made high-precision real-time data available in large quantities. Data assimilation (DA) is concerned with how to combine this data with ph…