The magic of danmaku: A social interaction perspective of gift sending on live streaming platforms. - Jilei Zhou; Jing Zhou 005; Ying Ding 004; Hansheng Wang 002 (Electron. Commer. Res. Appl., 2019)

Progressive principle component analysis for compressing deep convolutional neural networks. - Jing Zhou 005; Haobo Qi; Yu Chen; Hansheng Wang 002 (Neurocomputing, 2021)

Embedding Compression for Text Classification Using Dictionary Screening. - Jing Zhou 005; Xinru Jing; Muyu Liu; Hansheng Wang 002 (CoRR, 2022)

Asymptotic covariance estimation by Gaussian random perturbation. - Jing Zhou 005; Wei Lan; Hansheng Wang 002 (Comput. Stat. Data Anal., 2022)

High-risk Factor Prediction in Lung Cancer Using Thin CT Scans: An Attention-Enhanced Graph Convolutional Network Approach. - Xiaotong Fu; Xiangyu Meng; Jing Zhou 005; Ying Ji (BIBM, 2023)

Supervised Domain Adaptation for Recognizing Retinal Diseases from Wide-Field Fundus Images. - Qijie Wei; Jingyuan Yang 004; Bo Wang 011; Jinrui Wang; Jianchun Zhao; Xinyu Zhao; Sheng Yang; Niranchana Manivannan; Youxin Chen; Dayong Ding; Jing Zhou 005; Xirong Li 001 (BIBM, 2023)

Compressing the Embedding Matrix by a Dictionary Screening Approach in Text Classification. - Jing Zhou 005; Xinru Jing; Muyu Liu; Hansheng Wang 002 (PAKDD (1), 2023)

Automatic Discovery of Controversial Legal Judgments by an Entropy-Based Measurement (S). - Jing Zhou 005; Shan Leng; Fang Wang; Hansheng Wang 002 (SEKE, 2023)

Adaptive Fusion of Radiomics and Deep Features for Lung Adenocarcinoma Subtype Recognition. - Jing Zhou 005; Xiaotong Fu; Xirong Li 001; Wei Feng; Zhang Zhang; Ying Ji (CoRR, 2023)

An ensemble deep learning model for risk stratification of invasive lung adenocarcinoma using thin-slice CT. - Jing Zhou 005; Bin Hu; Wei Feng; Zhang Zhang; Xiaotong Fu; Handie Shao; Hansheng Wang 002; Longyu Jin; Siyuan Ai; Ying Ji (npj Digit. Medicine, 2023)

RFDFM: A Deep Factorization Machine Network Model for Invasive Lung Adenocarcinoma Screening in CT Images. - Jing Zhou 005; Chengcheng Guo 001; Ying Ji (ECAI, 2024)

A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques. - Xuetong Li; Yuan Gao 026; Hong Chang; Danyang Huang; Yingying Ma; Rui Pan 004; Haobo Qi; Feifei Wang; Shuyuan Wu; Ke Xu; Jing Zhou 005; Xuening Zhu; et al. (CoRR, 2024)

Gaussian Mixture Models with Rare Events. - Xuetong Li; Jing Zhou 005; Hansheng Wang 002 (J. Mach. Learn. Res., 2024)

Confidence-Enhanced Semi-Supervised Learning for Mediastinal Neoplasm Segmentation. - Xiaotong Fu; Jing Zhou 005; Shuying Zhang; Ying Ji (BIBM, 2025)

DialogMedTab: A Dual-Modality Benchmark Dataset with Cross-Decoder Transformer (CDT) for Sentiment Analysis in Doctor-Patient Dialogues. - Guanjing Liu; Jing Zhou 005; Jing Liu (BIBM, 2025)

CALM: A Copula-Augmented Lightweight Deep Learning Model for Robust Pulmonary Function Assessment from CT Imaging. - Xiangyu Meng; Hang Yu; Jing Zhou 005; Bo Fu; Ying Ji (BIBM, 2025)

MAG-Net: A Multi-Task Deep Learning Framework for Thymic Tumor Diagnosis. - Shuying Zhang; Jing Zhou 005; Ying Ji (BIBM, 2025)

DSANet: 3D Deformable Slice-Aware Network with Adaptive Slice Grouping for Robust Pulmonary Nodule Detection. - Zhongyang Che; Jing Zhou 005; Zhi Tu; Ying Ji (ECAI, 2025)

High Resolution Image Classification with Rich Text Information Based on Graph Convolution Neural Network. - Siyi Han; Jing Zhou 005; Xuening Zhu; Zhe Li; Jie Li 002; Hansheng Wang 002; Yibing Gong (PAKDD (7), 2025)

Class-Distributed Learning for Multinomial Logistic Regression with High Dimensional Features and a Large Number of Classes. - Shuyuan Wu; Jing Zhou 005; Ke Xu; Hansheng Wang 002 (J. Comput. Graph. Stat., 2025)