More powerful tests for sparse high-dimensional covariances matrices. - Liuhua Peng; Song Xi Chen; Wen Zhou (J. Multivar. Anal., 2016)

Variable importance assessments and backward variable selection for multi-sample problems. - Liuhua Peng; Long Qu; Dan Nettleton (J. Multivar. Anal., 2021)

Uncertainty Quantification in Depth Estimation via Constrained Ordinal Regression. - Dongting Hu; Liuhua Peng; Tingjin Chu; Xiaoxing Zhang; Yinian Mao; Howard D. Bondell; Mingming Gong (ECCV (2), 2022)

Nonparametric feature selection by random forests and deep neural networks. - Xiaojun Mao; Liuhua Peng; Zhonglei Wang (Comput. Stat. Data Anal., 2022)

In-N-Out: Lifting 2D Diffusion Prior for 3D Object Removal via Tuning-Free Latents Alignment. - Dongting Hu; Huan Fu; Jiaxian Guo; Liuhua Peng; Tingjin Chu; Feng Liu 003; Tongliang Liu; Mingming Gong (NeurIPS, 2024)

Conformalized Multiple Testing after Data-dependent Selection. - Xiaoning Wang; Yuyang Huo; Liuhua Peng; Changliang Zou (NeurIPS, 2024)

Revisit Non-parametric Two-sample Testing as a Semi-supervised Learning Problem. - Xunye Tian; Liuhua Peng; Zhijian Zhou; Mingming Gong; Feng Liu (CoRR, 2024)

LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning. - Zhekai Du; Yinjie Min; Jingjing Li; Ke Lu; Changliang Zou; Liuhua Peng; Tingjin Chu; Mingming Gong (ICLR, 2025)

A Unified Data Representation Learning for Non-parametric Two-sample Testing. - Xunye Tian; Liuhua Peng; Zhijian Zhou; Mingming Gong; Arthur Gretton; Feng Liu 003 (UAI, 2025)

A Kernel Distribution Closeness Testing. - Zhijian Zhou; Liuhua Peng; Xunye Tian; Feng Liu (CoRR, 2025)