4 papers
Self-Normalized Inference for Constant-Stepsize Temporal-Difference Learning under Markovian Sampling
Min Zeng, Yichen Zhang, Xiaofeng Shao
Constant-stepsize temporal-difference (TD) learning is attractive for policy evaluation, but inference from a single Markov trajectory must account for serial dependence and a step…
Testing Equality of Conditional Distributions via Generative Models
Hanjia Gao, Linjun Huang, Yun Yang +1
We study the problem of testing whether two conditional distributions are equal using generative models. The proposed method learns a conditional generator from each sample and use…
Resampling-free Inference for Time Series via RKHS Embedding
Deep Ghoshal, Xiaofeng Shao
In this article, we study nonparametric inference problems in the context of multivariate or functional time series, including testing for goodness-of-fit, the presence of a change…
Testing Conditional Mean Independence Using Generative Neural Networks
Yi Zhang, Linjun Huang, Yun Yang +1
Conditional mean independence (CMI) testing is crucial for statistical tasks including model determination and variable importance evaluation. In this work, we introduce a novel po…