Hua Wang

发表

Cortical surface biomarkers for predicting cognitive outcomes using group l 2,1 norm

Li Shen, A. Saykin, Sungeun Kim, 2015, Neurobiology of Aging.

Robust Principal Component Analysis with Non-Greedy l1-Norm Maximization

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, IJCAI.

Simultaneous clustering of multi-type relational data via symmetric nonnegative matrix tri-factorization

Chris H. Q. Ding, Hua Wang, Heng Huang, 2011, CIKM '11.

Image annotation using multi-label correlated Green's function

Chris H. Q. Ding, Hua Wang, Heng Huang, 2009, 2009 IEEE 12th International Conference on Computer Vision.

Image Categorization Using Directed Graphs

Chris H. Q. Ding, Hua Wang, Heng Huang, 2010, ECCV.

From phenotype to genotype: a structured sparse learning framework for imaging genetics studies

Heng Huang, Hua Wang, Hua Wang, 2012 .

Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2012, RECOMB.

From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, Bioinform..

Robust and Discriminative Self-Taught Learning

Feiping Nie, Hua Wang, Heng Huang, 2013, ICML.

Learning Robust Multilabel Sample Specific Distances for Identifying HIV-1 Drug Resistance

Hua Wang, F. Nie, Kai Liu, 2019, J. Comput. Biol..

Identification of novel cortical surface biomarkers for predicting cognitive outcomes based on group-level` 2,1 norm

Li Shen, A. Saykin, Sungeun Kim, 2012 .

Learning high-dimensional correspondence via manifold learning and local approximation

Hua Wang, F. Nie, Changshui Zhang, 2014, Neural Computing and Applications.

Self-taught learning via exponential family sparse coding for cost-effective patient thought record categorization

F. Makedon, Hua Wang, Heng Huang, 2012, Personal and Ubiquitous Computing.

New l1-Norm Relaxations and Optimizations for Graph Clustering

Xuelong Li, Feiping Nie, Hua Wang, 2016, AAAI.

Unsupervised and semi-supervised learning via ℓ1-norm graph

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, 2011 International Conference on Computer Vision.

Learning Multi-instance Enriched Image Representations via Non-greedy Ratio Maximization of the l1-Norm Distances

Kai Liu, Feiping Nie, Hao Zhang, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Maximum Margin Multi-Instance Learning

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, NIPS.

Nonnegative Matrix Tri-factorization Based High-Order Co-clustering and Its Fast Implementation

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, 2011 IEEE 11th International Conference on Data Mining.

Self-taught learning via exponential family sparse coding for cost-effective patient thought record categorization

Fillia Makedon, Hua Wang, Heng Huang, 2012, Personal and Ubiquitous Computing.

Dyadic transfer learning for cross-domain image classification

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, 2011 International Conference on Computer Vision.

Cost effective depression patient thought record categorization via self-taught learning

Fillia Makedon, Hua Wang, Heng Huang, 2011, PETRA '11.

From Protein Sequence to Protein Function via Multi-Label Linear Discriminant Analysis

Heng Huang, Lin Yan, Chris Ding, 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Predicting Cognitive Declines Using Longitudinally Enriched Representations for Imaging Biomarkers

Feiping Nie, Hua Wang, Lyujian Lu, 2020, IEEE Transactions on Medical Imaging.

Predicting Cognitive Declines Using Longitudinally Enriched Representations for Imaging Biomarkers

Feiping Nie, Hua Wang, Lyujian Lu, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, Bioinform..

Early Active Learning via Robust Representation and Structured Sparsity

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2013, IJCAI.

Learning Deeply Enriched Representations of Longitudinal Imaging-Genetic Data to Predict Alzheimer’s Disease Progression

Hua Wang, Hoon Seo, 2021, 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Large-Scale Cross-Language Web Page Classification via Dual Knowledge Transfer Using Fast Nonnegative Matrix Trifactorization

Feiping Nie, Hua Wang, Heng Huang, 2015, ACM Trans. Knowl. Discov. Data.

Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, Bioinform..

Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2011, MICCAI.

Multi-label Linear Discriminant Analysis

Chris H. Q. Ding, Hua Wang, Heng Huang, 2010, ECCV.

Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2011, 2011 International Conference on Computer Vision.

Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2012, RECOMB.

Fast Nonnegative Matrix Tri-Factorization for Large-Scale Data Co-Clustering

Fillia Makedon, Feiping Nie, Hua Wang, 2011, IJCAI.

Self-Adaptive Skeleton Approaches to Detect Self-Organized Coalitions From Brain Functional Networks Through Probabilistic Mixture Models

Kai Liu, Bo Zhang, Xindong Wu, 2021, ACM Trans. Knowl. Discov. Data.

Cortical surface biomarkers for predicting cognitive outcomes using group l 2,1 norm

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2015, Neurobiology of Aging.

Joint Schatten $$p$$p-norm and $$\ell _p$$ℓp-norm robust matrix completion for missing value recovery

C. Ding, Hua Wang, Heng Huang, 2013, Knowledge and Information Systems.

Robust Matrix Completion via Joint Schatten p-Norm and lp-Norm Minimization

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2012, 2012 IEEE 12th International Conference on Data Mining.

Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments Over Progressions

Hua Wang, Li Shen, Heng Huang, 2019, IEEE Transactions on Biomedical Engineering.

Joint Multi-Modal Longitudinal Regression and Classification for Alzheimer’s Disease Prediction

Hua Wang, Heng Huang, Li Shen, 2019, IEEE Transactions on Medical Imaging.

Predicting Longitudinal Outcomes of Alzheimer’s Disease via a Tensor-Based Joint Classification and Regression Model

Hua Wang, Heng Huang, Li Shen, 2019, PSB.

Joint stage recognition and anatomical annotation of drosophila gene expression patterns

Chris H. Q. Ding, Hua Wang, Heng Huang, 2012, Bioinform..

Learning Robust Distance Metric with Side Information via Ratio Minimization of Orthogonally Constrained L21-Norm Distances

Kai Liu, Feiping Nie, Hua Wang, 2019, IJCAI.

Function-Function Correlated Multi-Label Protein Function Prediction over Interaction Networks

Chris H. Q. Ding, Hua Wang, Heng Huang, 2012, RECOMB.

Directed Graph Learning via High-Order Co-linkage Analysis

Chris H. Q. Ding, Hua Wang, Heng Huang, 2010, ECML/PKDD.

Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2011, SIGIR.

A multi-instance support vector machine with incomplete data for clinical outcome prediction of COVID-19

Hua Wang, Lodewijk Brand, L. Baker, 2021, BCB.

Task Balanced Multimodal Feature Selection to Predict the Progression of Alzheimer’s Disease

Hua Wang, Lodewijk Brand, Anthony Sun, 2020, 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE).

Emotion Detection via Discriminant Laplacian Embedding

Fillia Makedon, Hua Wang, Heng Huang, 2014, Universal Access in the Information Society.

Emotion detection via discriminative kernel method

Fillia Makedon, Hua Wang, Heng Huang, 2010, PETRA '10.

Multi-View Clustering and Feature Learning via Structured Sparsity

Feiping Nie, Hua Wang, Heng Huang, 2013, ICML.

Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence Adaptive Loss Minimization for Semi-Supervised Elastic Embedding

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2022 .

Learning Multi-Modal Biomarker Representations via Globally Aligned Longitudinal Enrichments

Hua Wang, Lyujian Lu, Saad Elbeleidy, 2020, AAAI.

Multimodal Neuroimaging Predictors for Cognitive Performance Using Structured Sparse Learning

Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, 2012, MBIA.

Integrating Static and Dynamic Data for Improved Prediction of Cognitive Declines Using Augmented Genotype-Phenotype Representations

Feiping Nie, Lodewijk Brand, Hoon Seo, 2021, AAAI.

Learning Semi-Supervised Representation Enrichment Using Longitudinal Imaging-Genetic Data

Hua Wang, Lodewijk Brand, Hoon Seo, 2020, 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer's Disease

Shannon L. Risacher, Andrew J. Saykin, Hua Wang, 2018, MICCAI.

Predicting progressions of cognitive outcomes via high-order multi-modal multi-task feature learning

Shannon L. Risacher, Andrew J. Saykin, Hua Wang, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction

Shannon L. Risacher, Andrew J. Saykin, Feiping Nie, 2012, NIPS.

Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization

Feiping Nie, Hua Wang, Heng Huang, 2014, ICML.

Drosophila Gene Expression Pattern Annotations via Multi-Instance Biological Relevance Learning

Hua Wang, Heng Huang, Xinbo Gao, 2016, AAAI.

Robust and discriminative distance for Multi-Instance Learning

Feiping Nie, Hua Wang, Heng Huang, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Low-Rank Tensor Completion with Spatio-Temporal Consistency

Feiping Nie, Hua Wang, Heng Huang, 2014, AAAI.

Multi-Label Classification: Inconsistency and Class Balanced K-Nearest Neighbor

Chris H. Q. Ding, Hua Wang, Heng Huang, 2010, AAAI.

Learning Robust Locality Preserving Projection via p-Order Minimization

Feiping Nie, Hua Wang, Heng Huang, 2015, AAAI.

Semi-supervised Robust Dictionary Learning via Efficient l-Norms Minimization

Feiping Nie, Hua Wang, Heng Huang, 2013, 2013 IEEE International Conference on Computer Vision.

Image annotation using bi-relational graph of images and semantic labels

Chris H. Q. Ding, Hua Wang, Heng Huang, 2011, CVPR 2011.

High-Order Co-Clustering via Strictly Orthogonal and Symmetric L1-Norm Nonnegative Matrix Tri-Factorization

Kai Liu, Hua Wang, Hua Wang, 2018, IJCAI.

Heterogeneous Visual Features Fusion via Sparse Multimodal Machine

Feiping Nie, Chris H. Q. Ding, Hua Wang, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Factor-Bounded Nonnegative Matrix Factorization

Hua Wang, Lodewijk Brand, Kai Liu, 2021, ACM Trans. Knowl. Discov. Data.

Chris H. Q. Ding, Hua Wang, Heng Huang, 2014, RECOMB.

Exact Sparse Orthogonal Dictionary Learning pdf

Kai Liu, Hua Wang, Yongjian Zhao, 2021, ArXiv.

Robust Multi-Relational Clustering via \ell_1-Norm Symmetric Nonnegative Matrix Factorization

Kai Liu, Hua Wang, Hua Wang, 2015, ACL.

Learning Strictly Orthogonal p-Order Nonnegative Laplacian Embedding via Smoothed Iterative Reweighted Method

Kai Liu, Feiping Nie, Hua Wang, 2019, IJCAI.

Globally and Locally Consistent Unsupervised Projection

Feiping Nie, Hua Wang, Heng Huang, 2014, AAAI.

Learning frame relevance for video classification

Yi Yang, Feiping Nie, Hua Wang, 2011, ACM Multimedia.

Learning Instance Specific Distance for Multi-Instance Classification

Feiping Nie, Hua Wang, Heng Huang, 2011, AAAI.

On Mean-Optimal Robust Linear Discriminant Analysis

Hua Wang, Xiangyu Li, 2022, 2022 IEEE International Conference on Data Mining (ICDM).