148 citations · 173 across the 9 of their papers we have counts for
9 papers
Cross-Semantic Transfer Learning for High-Dimensional Linear Regression
Jiancheng Jiang, Xuejun Jiang, Hongxia Jin
Current transfer learning methods for high-dimensional linear regression assume feature alignment across domains, restricting their applicability to semantically matched features.…
Partition-Insensitive Parallel ADMM Algorithm for High-dimensional Linear Models
Xiaofei Wu, Jiancheng Jiang, Zhimin Zhang
The parallel alternating direction method of multipliers (ADMM) algorithms have gained popularity in statistics and machine learning due to their efficient handling of large sample…
Nonnested model selection based on empirical likelihood
Jiancheng Jiang, Jiang Xuejun, Wang Haofeng
We propose an empirical likelihood ratio test for nonparametric model selection, where the competing models may be nested, nonnested, overlapping, misspecified, or correctly specif…
Feature Augmentation via Nonparametrics and Selection (FANS) in High Dimensional Classification
Jianqing Fan, Yang Feng, Jiancheng Jiang +1
We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifi…
Nonparametric tests of the Markov hypothesis in continuous-time models
Yacine Aït-Sahalia, Jianqing Fan, Jiancheng Jiang
We propose several statistics to test the Markov hypothesis for -mixing stationary processes sampled at discrete time intervals. Our tests are based on the Chapman--Kolmogorov e…
Estimation in additive models with highly or nonhighly correlated covariates
Jiancheng Jiang, Yingying Fan, Jianqing Fan
Motivated by normalizing DNA microarray data and by predicting the interest rates, we explore nonparametric estimation of additive models with highly correlated covariates. We intr…