Unsupervised Feature Selection with Structured Graph Optimization. - Feiping Nie 001; Wei Zhu 015; Xuelong Li 001 (AAAI, 2016)

Unsupervised Large Graph Embedding. - Feiping Nie 001; Wei Zhu 015; Xuelong Li 001 (AAAI, 2017)

Fast Spectral Clustering with efficient large graph construction. - Wei Zhu 015; Feiping Nie 001; Xuelong Li 001 (ICASSP, 2017)

Predicting Parkinson's Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data. - Weijian Li 001; Wei Zhu 015; Earl Ray Dorsey; Jiebo Luo 001 (ICDM, 2020)

Modeling Heterogeneity in Feature Selection for MCI Classification. - Wei Zhu 015; Feng Shi 001; Jiebo Luo 001 (ISBI, 2020)

Alleviating the Incompatibility Between Cross Entropy Loss and Episode Training for Few-Shot Skin Disease Classification. - Wei Zhu 015; Haofu Liao; Wenbin Li 006; Weijian Li 001; Jiebo Luo 001 (MICCAI (6), 2020)

Unifying Specialist Image Embedding into Universal Image Embedding. - Yang Feng 001; Futang Peng; Xu Zhang 022; Wei Zhu 015; Shanfeng Zhang; Howard Zhou; Zhen Li 028; Tom Duerig; Shih-Fu Chang; Jiebo Luo 001 (CoRR, 2020)

Decision Tree SVM: An extension of linear SVM for non-linear classification. - Feiping Nie 001; Wei Zhu 015; Xuelong Li 001 (Neurocomputing, 2020)

Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach. - Haitian Zheng; Kefei Wu; Jong-Hwi Park; Wei Zhu 015; Jiebo Luo 001 (IEEE BigData, 2021)

Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization. - Wei Zhu 015; Haitian Zheng; Haofu Liao; Weijian Li 001; Jiebo Luo 001 (ICCV, 2021)

Federated Learning of Molecular Properties in a Heterogeneous Setting. - Wei Zhu 015; Andrew D. White; Jiebo Luo 001 (CoRR, 2021)

Temperature network for few-shot learning with distribution-aware large-margin metric. - Wei Zhu 015; Wenbin Li 006; Haofu Liao; Jiebo Luo 001 (Pattern Recognit., 2021)

Structured Graph Optimization for Unsupervised Feature Selection. - Feiping Nie 001; Wei Zhu 015; Xuelong Li 001 (IEEE Trans. Knowl. Data Eng., 2021)

Deep Federated Anomaly Detection for Multivariate Time Series Data. - Wei Zhu 015; Dongjin Song; Yuncong Chen; Wei Cheng 002; Bo Zong; Takehiko Mizoguchi; Cristian Lumezanu; Haifeng Chen; Jiebo Luo 001 (IEEE Big Data, 2022)

Localized Adversarial Domain Generalization. - Wei Zhu 015; Le Lu 001; Jing Xiao 006; Mei Han; Jiebo Luo 001; Adam P. Harrison (CVPR, 2022)

Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis. - Wei Zhu 015; Zihe Zheng; Haitian Zheng; Hanjia Lyu; Jiebo Luo 001 (ICPR, 2022)

Federated Medical Image Analysis with Virtual Sample Synthesis. - Wei Zhu 015; Jiebo Luo 001 (MICCAI (3), 2022)

Federated learning of molecular properties with graph neural networks in a heterogeneous setting. - Wei Zhu 015; Jiebo Luo 001; Andrew D. White (Patterns, 2022)

Unsupervised Large Graph Embedding Based on Balanced and Hierarchical K-Means. - Feiping Nie 001; Wei Zhu 015; Xuelong Li 001 (IEEE Trans. Knowl. Data Eng., 2022)

Remote Medication Status Prediction for Individuals with Parkinson's Disease using Time-series Data from Smartphones. - Weijian Li 001; Wei Zhu 015; Earl Ray Dorsey; Jiebo Luo 001 (ICDH, 2023)

SegPrompt: Using Segmentation Map as a Better Prompt to Finetune Deep Models for Kidney Stone Classification. - Wei Zhu 015; Runtao Zhou; Yuan Yao; Timothy Douglas Campbell; Rajat Kumar Jain; Jiebo Luo 001 (MIDL, 2023)

SegPrompt: Using Segmentation Map as a Better Prompt to Finetune Deep Models for Kidney Stone Classification. - Wei Zhu 015; Runtao Zhou; Yao Yuan; Timothy Campbell; Rajat Kumar Jain; Jiebo Luo 001 (CoRR, 2023)

Unsupervised anomaly detection by densely contrastive learning for time series data. - Wei Zhu 015; Weijian Li 001; Earl Ray Dorsey; Jiebo Luo 001 (Neural Networks, 2023)

Low-Rank Continual Pyramid Vision Transformer: Incrementally Segment Whole-Body Organs in CT with Light-Weighted Adaptation. - Vince Zhu; Zhanghexuan Ji; Dazhou Guo; Puyang Wang; Yingda Xia; Le Lu 001; Xianghua Ye; Wei Zhu 015; Dakai Jin (MICCAI (8), 2024)