Inference of Dynamic Graph Changes for Functional Connectome. - Dingjue Ji; Junwei Lu; Yiliang Zhang; Siyuan Gao; Hongyu Zhao 003 (AISTATS, 2020)

Efficient Designs Of SLOPE Penalty Sequences In Finite Dimension. - Yiliang Zhang; Zhiqi Bu (AISTATS, 2021)

Assessing Fairness in the Presence of Missing Data. - Yiliang Zhang; Qi Long (NeurIPS, 2021)

Comparison of methods for estimating genetic correlation between complex traits using GWAS summary statistics. - Yiliang Zhang; Youshu Cheng; Wei Jiang 019; Yixuan Ye; Qiongshi Lu; Hongyu Zhao 003 (Briefings Bioinform., 2021)

Fairness in Missing Data Imputation. - Yiliang Zhang; Qi Long (CoRR, 2021)

A general kernel boosting framework integrating pathways for predictive modeling based on genomic data. - Li Zeng; Zhaolong Yu; Yiliang Zhang; Hongyu Zhao 003 (BCB, 2022)

An Unconstrained Layer-Peeled Perspective on Neural Collapse. - Wenlong Ji; Yiping Lu 001; Yiliang Zhang; Zhun Deng; Weijie J. Su (ICLR, 2022)

Combating Noisy-Labeled and Imbalanced Data by Two Stage Bi-Dimensional Sample Selection. - Yiliang Zhang; Yang Lu 009; Bo Han 003; Yiu-ming Cheung; Hanzi Wang (CoRR, 2022)

Label-Noise Learning with Intrinsically Long-Tailed Data. - Yang Lu 009; Yiliang Zhang; Bo Han 003; Yiu-Ming Cheung; Hanzi Wang (ICCV, 2023)

MISNN: Multiple Imputation via Semi-parametric Neural Networks. - Zhiqi Bu; Zongyu Dai; Yiliang Zhang; Qi Long (PAKDD (1), 2023)

Benchmarking of local genetic correlation estimation methods using summary statistics from genome-wide association studies. - Chi Zhang; Yiliang Zhang; Yunxuan Zhang; Hongyu Zhao 003 (Briefings Bioinform., 2023)

Federated Learning with Extremely Noisy Clients via Negative Distillation. - Yang Lu 009; Lin Chen; Yonggang Zhang 003; Yiliang Zhang; Bo Han 003; Yiu-ming Cheung; Hanzi Wang (AAAI, 2024)

Joint modeling of human cortical structure: Genetic correlation network and composite-trait genetic correlation. - Jiangnan Shen; Yiliang Zhang; Zhaohan Zhu; Youshu Cheng; Biao Cai; Yize Zhao; Hongyu Zhao 003 (NeuroImage, 2024)

Label-noise learning via uncertainty-aware neighborhood sample selection. - Yiliang Zhang; Yang Lu 009; Hanzi Wang (Pattern Recognit. Lett., 2024)

A Hessian-informed hyperparameter optimization for differential learning rate. - Shiyun Xu; Zhiqi Bu; Yiliang Zhang; Ian J. Barnett (CoRR, 2025)