Cost Sensitive Ranking Support Vector Machine for Multi-label Data Learning. - Peng Cao 001; Xiaoli Liu 001; Dazhe Zhao; Osmar R. Zaïane (HIS, 2016)

Sparse Learning and Hybrid Probabilistic Oversampling for Alzheimer's Disease Diagnosis. - Peng Cao 001; Xiaoli Liu 001; Dazhe Zhao; Osmar R. Zaïane (HIS, 2016)

Group Guided Sparse Group Lasso Multi-task Learning for Cognitive Performance Prediction of Alzheimer's Disease. - Xiaoli Liu 001; Peng Cao 001; Jinzhu Yang; Dazhe Zhao; Osmar R. Zaïane (BI, 2017)

Sparse Multi-kernel Based Multi-task Learning for Joint Prediction of Clinical Scores and Biomarker Identification in Alzheimer's Disease. - Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Dazhe Zhao; Osmar R. Zaïane (MICCAI (3), 2017)

Nonlinearity-aware based dimensionality reduction and over-sampling for AD/MCI classification from MRI measures. - Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Dazhe Zhao; Min Huang 001; Jian Zhang; Osmar R. Zaïane (Comput. Biol. Medicine, 2017)

A ℓ2, 1 norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD. - Peng Cao 001; Xiaoli Liu 001; Jian Zhang; Wei Li 117; Dazhe Zhao; Min Huang 001; Osmar R. Zaïane (Comput. Methods Programs Biomed., 2017)

ℓ2, 1 norm regularized multi-kernel based joint nonlinear feature selection and over-sampling for imbalanced data classification. - Peng Cao 001; Xiaoli Liu 001; Jian Zhang; Dazhe Zhao; Min Huang 001; Osmar R. Zaïane (Neurocomputing, 2017)

A multi-kernel based framework for heterogeneous feature selection and over-sampling for computer-aided detection of pulmonary nodules. - Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Dazhe Zhao; Wei Li 117; Min Huang 001; Osmar R. Zaïane (Pattern Recognit., 2017)

Modeling Alzheimer's disease cognitive scores using multi-task sparse group lasso. - Xiaoli Liu 001; André R. Gonçalves 001; Peng Cao 001; Dazhe Zhao; Arindam Banerjee 001 (Comput. Medical Imaging Graph., 2018)

Linearized and Kernelized Sparse Multitask Learning for Predicting Cognitive Outcomes in Alzheimer's Disease. - Xiaoli Liu 001; Peng Cao 001; Jinzhu Yang; Dazhe Zhao (Comput. Math. Methods Medicine, 2018)

Generalized fused group lasso regularized multi-task feature learning for predicting cognitive outcomes in Alzheimers disease. - Peng Cao 001; Xiaoli Liu 001; Hezi Liu; Jinzhu Yang; Dazhe Zhao; Min Huang 001; Osmar R. Zaïane (Comput. Methods Programs Biomed., 2018)

ℓ2, 1-ℓ1 regularized nonlinear multi-task representation learning based cognitive performance prediction of Alzheimer's disease. - Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Dazhe Zhao; Min Huang 001; Osmar R. Zaïane (Pattern Recognit., 2018)

Modeling Alzheimer's Disease Progression with Fused Laplacian Sparse Group Lasso. - Xiaoli Liu 001; Peng Cao 001; André R. Gonçalves 001; Dazhe Zhao; Arindam Banerjee 001 (ACM Trans. Knowl. Discov. Data, 2018)

Two-block vs. Multi-block ADMM: An empirical evaluation of convergence. - André R. Gonçalves 001; Xiaoli Liu 001; Arindam Banerjee 001 (CoRR, 2019)

Fused Group Lasso Regularized Multi-Task Feature Learning and Its Application to the Cognitive Performance Prediction of Alzheimer's Disease. - Xiaoli Liu 001; Peng Cao 001; Jianzhong Wang; Jun Kong 004; Dazhe Zhao (Neuroinformatics, 2019)

SP-MTFL: A self paced multi-task feature learning method for cognitive performance predicting of Alzheimer's disease. - Xiaoli Liu 001; Jiali Li; Peng Cao 001 (ISICDM, 2020)

Modeling Disease Progression with Deep Neural Networks. - Xiaoli Liu 001; Jiali Li; Peng Cao 001 (ISICDM, 2020)

S-GCN: A siamese spectral graph convolutions on brain connectivity networks. - Xiaoli Liu 001; Jiali Li; Peng Cao 001 (ISICDM, 2020)

Group Guided Fused Laplacian Sparse Group Lasso for Modeling Alzheimer's Disease Progression. - Xiaoli Liu 001; Jianzhong Wang; Fulong Ren; Jun Kong 004 (Comput. Math. Methods Medicine, 2020)

An Intelligent Multi-View Active Learning Method Based on a Double-Branch Network. - Fucong Liu; Tongzhou Zhang 001; Caixia Zheng; Yuanyuan Cheng; Xiaoli Liu 001; Miao Qi; Jun Kong 004; Jianzhong Wang (Entropy, 2020)

Spatiotemporal Interaction Residual Networks with Pseudo3D for Video Action Recognition. - Jianyu Chen; Jun Kong 004; Hui Sun; Hui Xu; Xiaoli Liu 001; Yinghua Lu; Caixia Zheng (Sensors, 2020)

Temporal Graph Representation Learning for Autism spectrum disorder Brain Networks. - Peng Cao 001; Guangqi Wen; Lanting Li; Xiaoli Liu 001; Jinzhu Yang; Osmar Zaïane (BIBM, 2021)

Rethinking modeling Alzheimer's disease progression from a multi-task learning perspective with deep recurrent neural network. - Wei Liang; Kai Zhang; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Comput. Biol. Medicine, 2021)

Dual feature correlation guided multi-task learning for Alzheimer's disease prediction. - Shanshan Tang; Peng Cao 001; Min Huang 001; Xiaoli Liu 001; Osmar R. Zaïane (Comput. Biol. Medicine, 2022)

Modeling the dynamic brain network representation for autism spectrum disorder diagnosis. - Peng Cao 001; Guangqi Wen; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Medical Biol. Eng. Comput., 2022)

TE-HI-GCN: An Ensemble of Transfer Hierarchical Graph Convolutional Networks for Disorder Diagnosis. - Lanting Li; Hao Jiang; Guangqi Wen; Peng Cao 001; MingYi Xu; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Neuroinformatics, 2022)

Gaze Estimation via the Joint Modeling of Multiple Cues. - Wenhe Chen; Hui Xu; Chao Zhu 002; Xiaoli Liu 001; Yinghua Lu; Caixia Zheng; Jun Kong 004 (IEEE Trans. Circuits Syst. Video Technol., 2022)

csl-MTFL: Multi-task Feature Learning with Joint Correlation Structure Learning for Alzheimer's Disease Cognitive Performance Prediction. - Wei Liang; Kai Zhang; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (ADMA (3), 2023)

Towards Time-Variant-Aware Link Prediction in Dynamic Graph Through Self-supervised Learning. - Guangqi Wen; Peng Cao 001; Zhiyong Jin; Ruoxian Song; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (ADMA (4), 2023)

Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation. - Zhiqiang Shen; Peng Cao 001; Hua Yang; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (IJCAI, 2023)

Lesion-Aware Contrastive Learning for Diabetic Retinopathy Diagnosis. - Shuai Cheng; Qingshan Hou; Peng Cao 001; Jinzhu Yang; Xiaoli Liu 001; Osmar R. Zaïane (MICCAI (7), 2023)

Modeling Alzheimers' Disease Progression from Multi-task and Self-supervised Learning Perspective with Brain Networks. - Wei Liang; Kai Zhang; Peng Cao 001; Pengfei Zhao; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (MICCAI (1), 2023)

A Reference-free Self-supervised Domain Adaptation Framework for Low-quality Fundus Image Enhancement. - Qingshan Hou; Peng Cao 001; Jiaqi Wang 013; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (ACM Multimedia, 2023)

MS-SSD: multi-scale single shot detector for ship detection in remote sensing images. - Guangqi Wen; Peng Cao 001; Haonan Wang; Hanlin Chen; Xiaoli Liu 001; Jinghui Xu; Osmar R. Zaïane (Appl. Intell., 2023)

Exploiting task relationships for Alzheimer's disease cognitive score prediction via multi-task learning. - Wei Liang; Kai Zhang; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Comput. Biol. Medicine, 2023)

Self-supervised Domain Adaptation for Breaking the Limits of Low-quality Fundus Image Quality Enhancement. - Qingshan Hou; Peng Cao 001; Jiaqi Wang 013; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (CoRR, 2023)

Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentation. - Haonan Wang; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar Zaïane (CoRR, 2023)

A unified framework of graph structure learning, graph generation and classification for brain network analysis. - Peng Cao 001; Guangqi Wen; Wenju Yang; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Appl. Intell., 2023)

Exploring interpretable graph convolutional networks for autism spectrum disorder diagnosis. - Lanting Li; Guangqi Wen; Peng Cao 001; Xiaoli Liu 001; Osmar R. Zaïane; Jinzhu Yang (Int. J. Comput. Assist. Radiol. Surg., 2023)

GeoFed: A Geography-Aware Federated Learning Approach for Vehicular Visual Crowdsensing. - Xinli Hao; Wenjun Zhang 013; Xiaoli Liu 001; Chao Zhu 002; Sasu Tarkoma (ICC, 2024)

A Clinical-Oriented Multi-level Contrastive Learning Method for Disease Diagnosis in Low-Quality Medical Images. - Qingshan Hou; Shuai Cheng; Peng Cao 001; Jinzhu Yang; Xiaoli Liu 001; Yih Chung Tham; Osmar R. Zaïane (MICCAI (3), 2024)

A Clinical-Oriented Lightweight Network for High-Resolution Medical Image Enhancement. - Yaqi Wang 004; Leqi Chen; Qingshan Hou; Peng Cao 001; Jinzhu Yang; Xiaoli Liu 001; Osmar R. Zaïane (MICCAI (3), 2024)

Progressively Correcting Soft Labels via Teacher Team for Knowledge Distillation in Medical Image Segmentation. - Yaqi Wang 004; Peng Cao 001; Qingshan Hou; Linqi Lan; Jinzhu Yang; Xiaoli Liu 001; Osmar R. Zaïane (MICCAI (9), 2024)

Label correlation guided discriminative label feature learning for multi-label chest image classification. - Kai Zhang; Wei Liang; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Comput. Methods Programs Biomed., 2024)

A Collaborative Self-Supervised Domain Adaptation for Low-Quality Medical Image Enhancement. - Qingshan Hou; Yaqi Wang 004; Peng Cao 001; Shuai Cheng; Linqi Lan; Jinzhu Yang; Xiaoli Liu 001; Osmar R. Zaïane (IEEE Trans. Medical Imaging, 2024)

FundusGAN: A Hierarchical Feature-Aware Generative Framework for High-Fidelity Fundus Image Generation. - Qingshan Hou; Meng Wang 001; Peng Cao 001; Ke Zou; Xiaoli Liu 001; Huazhu Fu; Osmar R. Zaïane (CoRR, 2025)

A Reference-Free Quality Enhancement Framework for Low-Quality Fundus Images. - Qingshan Hou; Yaqi Wang 004; Linqi Lan; Peng Cao 001; Jinzhu Yang; Xiaoli Liu 001; Meng Wang 001; Yih Chung Tham; Osmar R. Zaïane (IEEE Trans. Circuits Syst. Video Technol., 2025)

SynMatch: Rethinking Consistency in Medical Image Segmentation with Sparse Annotations. - Zhiqiang Shen; Peng Cao 001; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (CoRR, 2025)