Hua Wang

According to our database, Hua Wang authored at least 97 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Toward Robust Discriminative Projections Learning Against Adversarial Patch Attacks.

Zheng Wang, Feiping Nie, Hua Wang, Heng Huang, Fei Wang

IEEE Trans. Neural Networks Learn. Syst., December, 2024

On Mean-Optimal Robust Linear Discriminant Analysis.

Xiangyu Li, Hua Wang

ACM Trans. Knowl. Discov. Data, September, 2024

A linear primal-dual multi-instance SVM for big data classifications.

Lodewijk Brand, Hoon Seo, Lauren Zoe Baker, Carla Ellefsen, Jackson Sargent, Hua Wang

Knowl. Inf. Syst., January, 2024

2023

Fast Multi-Modal Multi-Instance Support Vector Machine for Fine-grained Chest X-ray Recognition.

Hoon Seo, Hua Wang

Proceedings of the IEEE International Conference on Data Mining, 2023

Enriched Representation Learning for Longitudinal Chest X-ray Analysis: A Novel Approach for Improved Disease Detection and Localization.

Xiangyu Li, Armand Ovanessians, Hua Wang

Proceedings of the IEEE International Conference on Data Mining, 2023

Discovering Protein Interactions and Repurposing Drugs in SARS-CoV-2 (COVID-19) via Learning on Robust Multipartite Graphs.

Xiangyu Li, Armand Ovanessians, Hua Wang

Proceedings of the IEEE International Conference on Data Mining, 2023

Beyond the Simplex: Hadamard-Infused Deep Sparse Representations for Enhanced Similarity Measures.

Xiangyu Li, Umberto Gherardi, Armand Ovanessians, Hua Wang

Proceedings of the IEEE International Conference on Knowledge Graph, 2023

2022

Real-time recognition of team behaviors by multisensory graph-embedded robot learning.

Brian Reily, Peng Gao, Fei Han, Hua Wang, Hao Zhang

Int. J. Robotics Res., 2022

Scaling multi-instance support vector machine to breast cancer detection on the BreaKHis dataset.

Hoon Seo, Lodewijk Brand, Lucia Saldana Barco, Hua Wang

Bioinform., 2022

Adaptive Principal Component Analysis.

Xiangyu Li, Hua Wang

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Scalable Multi-Instance Multi-Shape Support Vector Machine for Whole Slide Breast Histopathology.

Hoon Seo, Lodewijk Brand, Lucia Saldana Barco, Hua Wang

Proceedings of the IEEE International Conference on Knowledge Graph, 2022

2021

Predicting Cognitive Declines Using Longitudinally Enriched Representations for Imaging Biomarkers.

Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang, Feiping Nie

IEEE Trans. Medical Imaging, 2021

Factor-Bounded Nonnegative Matrix Factorization.

Kai Liu, Xiangyu Li, Zhihui Zhu, Lodewijk Brand, Hua Wang

ACM Trans. Knowl. Discov. Data, 2021

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

Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang, Li Shen, Heng Huang

IEEE Trans. Biomed. Eng., 2021

Robust Real-Time Group Activity Recognition of Robot Teams.

Lyujian Lu, Hua Wang, Brian Reily, Hao Zhang

IEEE Robotics Autom. Lett., 2021

A Linear Primal-Dual Multi-Instance SVM for Big Data Classifications.

Lodewijk Brand, Lauren Zoe Baker, Carla Ellefsen, Jackson Sargent, Hua Wang

Proceedings of the IEEE International Conference on Data Mining, 2021

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

Hoon Seo, Hua Wang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

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

Lodewijk Brand, Lauren Zoe Baker, Hua Wang

Proceedings of the BCB '21: 12th ACM International Conference on Bioinformatics, 2021

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

Hoon Seo, Lodewijk Brand, Hua Wang, Feiping Nie

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

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

Lodewijk Brand, Kai Nichols, Hua Wang, Li Shen, Heng Huang

IEEE Trans. Medical Imaging, 2020

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

Lodewijk Brand, Xue Yang, Kai Liu, Saad Elbeleidy, Hua Wang, Hao Zhang, Feiping Nie

J. Comput. Biol., 2020

Predicting Longitudinal Outcomes of Alzheimer's Disease via a Tensor-Based Joint Classification andRegression Model.

Lodewijk Brand, Kai Nichols, Hua Wang, Heng Huang, Li Shen

Proceedings of the Pacific Symposium on Biocomputing 2020, 2020

Predicting Cognitive Declines Using Longitudinally Enriched Representations for Imaging Biomarkers.

Lyujian Lu, Hua Wang, Saad Elbeleidy, Feiping Nie

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

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

Hoon Seo, Lodewijk Brand, Hua Wang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

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

Lodewijk Brand, Braedon O'Callaghan, Anthony Sun, Hua Wang

Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

Learning Multi-Modal Biomarker Representations via Globally Aligned Longitudinal Enrichments.

Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Robust Linear Discriminant Analysis Using Ratio Minimization of L1, 2-Norms.

Feiping Nie, Hua Wang, Zheng Wang, Heng Huang

CoRR, 2019

Spherical Principal Component Analysis.

Kai Liu, Qiuwei Li, Hua Wang, Gongguo Tang

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Learning Robust Multi-label Sample Specific Distances for Identifying HIV-1 Drug Resistance.

Lodewijk Brand, Xue Yang, Kai Liu, Saad El Beleidy, Hua Wang, Hao Zhang

Proceedings of the Research in Computational Molecular Biology, 2019

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

Haoxuan Yang, Kai Liu, Hua Wang, Feiping Nie

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

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

Kai Liu, Lodewijk Brand, Hua Wang, Feiping Nie

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Visual Place Recognition via Robust ℓ2-Norm Distance Based Holism and Landmark Integration.

Kai Liu, Hua Wang, Fei Han, Hao Zhang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Learning of Holism-Landmark Graph Embedding for Place Recognition in Long-Term Autonomy.

Fei Han, Saad El Beleidy, Hua Wang, Cang Ye, Hao Zhang

IEEE Robotics Autom. Lett., 2018

Sequence-based sparse optimization methods for long-term loop closure detection in visual SLAM.

Fei Han, Hua Wang, Guoquan Huang, Hao Zhang

Auton. Robots, 2018

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

Lodewijk Brand, Hua Wang, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

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

Lyujian Lu, Hua Wang, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Multiple incomplete views clustering via non-negative matrix factorization with its application in Alzheimer's disease analysis.

Kai Liu, Hua Wang, Shannon L. Risacher, Andrew J. Saykin, Li Shen

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

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

Kai Liu, Hua Wang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Learning Multi-Instance Enriched Image Representations via Non-Greedy Ratio Maximization of the l1-Norm Distances.

Kai Liu, Hua Wang, Feiping Nie, Hao Zhang

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Learning Integrated Holism-Landmark Representations for Long-Term Loop Closure Detection.

Fei Han, Hua Wang, Hao Zhang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

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

Hua Wang, Lin Yan, Heng Huang, Chris H. Q. Ding

IEEE ACM Trans. Comput. Biol. Bioinform., 2017

Semi-Supervised Classifications via Elastic and Robust Embedding.

Yun Liu, Yiming Guo, Hua Wang, Feiping Nie, Heng Huang

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Robust Multimodal Sequence-Based Loop Closure Detection via Structured Sparsity.

Hao Zhang, Fei Han, Hua Wang

Proceedings of the Robotics: Science and Systems XII, University of Michigan, Ann Arbor, Michigan, USA, June 18, 2016

Enforcing Template Representability and Temporal Consistency for Adaptive Sparse Tracking.

Xue Yang, Fei Han, Hua Wang, Hao Zhang

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

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

Hua Wang, Cheng Deng, Hao Zhang, Xinbo Gao, Heng Huang

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

New l1-Norm Relaxations and Optimizations for Graph Clustering.

Feiping Nie, Hua Wang, Cheng Deng, Xinbo Gao, Xuelong Li, Heng Huang

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

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

Hua Wang, Feiping Nie, Heng Huang

ACM Trans. Knowl. Discov. Data, 2015

Joint Schatten p-norm and ℓ_p-norm robust matrix completion for missing value recovery.

Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding

Knowl. Inf. Syst., 2015

Correlated Protein Function Prediction via Maximization of Data-Knowledge Consistency.

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

J. Comput. Biol., 2015

Learning Robust Locality Preserving Projection via p-Order Minimization.

Hua Wang, Feiping Nie, Heng Huang

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Emotion Detection via Discriminant Laplacian Embedding.

Hua Wang, Heng Huang, Fillia Makedon

Univers. Access Inf. Soc., 2014

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

Hua Wang, Heng Huang, Monica Basco, Molly Lopez, Fillia Makedon

Pers. Ubiquitous Comput., 2014

Learning high-dimensional correspondence via manifold learning and local approximation.

Chenping Hou, Feiping Nie, Hua Wang, Dongyun Yi, Changshui Zhang

Neural Comput. Appl., 2014

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

Hua Wang, Feiping Nie, Heng Huang

Proceedings of the 31th International Conference on Machine Learning, 2014

Low-Rank Tensor Completion with Spatio-Temporal Consistency.

Hua Wang, Feiping Nie, Heng Huang

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Globally and Locally Consistent Unsupervised Projection.

Hua Wang, Feiping Nie, Heng Huang

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

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

Hua Wang, Heng Huang, Chris H. Q. Ding, Feiping Nie

J. Comput. Biol., 2013

Function-Function Correlated Multi-label Protein Function Prediction over Interaction Networks.

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

J. Comput. Biol., 2013

Protein Function Prediction via Laplacian Network Partitioning Incorporating Function Category Correlations.

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

Proceedings of the IJCAI 2013, 2013

Early Active Learning via Robust Representation and Structured Sparsity.

Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding

Proceedings of the IJCAI 2013, 2013

Adaptive Loss Minimization for Semi-Supervised Elastic Embedding.

Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding

Proceedings of the IJCAI 2013, 2013

Multi-View Clustering and Feature Learning via Structured Sparsity.

Hua Wang, Feiping Nie, Heng Huang

Proceedings of the 30th International Conference on Machine Learning, 2013

Robust and Discriminative Self-Taught Learning.

Hua Wang, Feiping Nie, Heng Huang

Proceedings of the 30th International Conference on Machine Learning, 2013

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

Hua Wang, Feiping Nie, Weidong Cai, Heng Huang

Proceedings of the IEEE International Conference on Computer Vision, 2013

Heterogeneous Visual Features Fusion via Sparse Multimodal Machine.

Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012

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

Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen

Bioinform., 2012

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

Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen

Bioinform., 2012

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

Hua Wang, Feiping Nie, Heng Huang, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen

Bioinform., 2012

Joint stage recognition and anatomical annotation of <i>drosophila</i> gene expression patterns.

Xiao Cai, Hua Wang, Heng Huang, Chris H. Q. Ding

Bioinform., 2012

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

Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Andrew J. Saykin, Li Shen

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Multimodal Neuroimaging Predictors for Cognitive Performance Using Structured Sparse Learning.

Jingwen Yan, Shannon L. Risacher, Sungeun Kim, Jacqueline C. Simon, Taiyong Li, Jing Wan, Hua Wang, Heng Huang, Andrew J. Saykin, Li Shen

Proceedings of the Multimodal Brain Image Analysis - Second International Workshop, 2012

Simultaneous Image Annotation and Geo-Tag Prediction via Correlation Guided Multi-task Learning.

Hua Wang, Dhiraj Joshi, Jiebo Luo, Heng Huang, Minwoo Park

Proceedings of the 2012 IEEE International Symposium on Multimedia, 2012

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

Feiping Nie, Hua Wang, Xiao Cai, Heng Huang, Chris H. Q. Ding

Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Simultaneous Image Classification and Annotation via Biased Random Walk on Tri-relational Graph.

Xiao Cai, Hua Wang, Heng Huang, Chris H. Q. Ding

Proceedings of the Computer Vision - ECCV 2012, 2012

Robust and discriminative distance for Multi-Instance Learning.

Hua Wang, Feiping Nie, Heng Huang

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

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

Hua Wang, Heng Huang, Feiping Nie, Chris H. Q. Ding

Proceedings of the Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2011

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

Hua Wang, Heng Huang, Monica Basco, Molly Lopez, Fillia Makedon

Proceedings of the PETRA 2011, 2011

Maximum Margin Multi-Instance Learning.

Hua Wang, Heng Huang, Farhad Kamangar, Feiping Nie, Chris H. Q. Ding

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Learning frame relevance for video classification.

Hua Wang, Feiping Nie, Heng Huang, Yi Yang

Proceedings of the 19th International Conference on Multimedia 2011, Scottsdale, AZ, USA, November 28, 2011

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

Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011

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

Hua Wang, Feiping Nie, Heng Huang, Fillia Makedon

Proceedings of the IJCAI 2011, 2011

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

Feiping Nie, Heng Huang, Chris H. Q. Ding, Dijun Luo, Hua Wang

Proceedings of the IJCAI 2011, 2011

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

Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

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

Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Chris H. Q. Ding, Andrew J. Saykin, Li Shen

Proceedings of the IEEE International Conference on Computer Vision, 2011

Dyadic transfer learning for cross-domain image classification.

Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding

Proceedings of the IEEE International Conference on Computer Vision, 2011

Unsupervised and semi-supervised learning via ℓ1-norm graph.

Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding

Proceedings of the IEEE International Conference on Computer Vision, 2011

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

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

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

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

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

Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

Learning Instance Specific Distance for Multi-Instance Classification.

Hua Wang, Feiping Nie, Heng Huang

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Directed Graph Learning via High-Order Co-linkage Analysis.

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

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Emotion detection via discriminative kernel method.

Hua Wang, Heng Huang, Yanzi Hu, Mindi Anderson, Pamela Rollins, Fillia Makedon

Proceedings of the 3rd International Conference on Pervasive Technologies Related to Assistive Environments, 2010

Multi-label Feature Transform for Image Classifications.

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

Proceedings of the Computer Vision, 2010

Image Categorization Using Directed Graphs.

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

Proceedings of the Computer Vision, 2010

Multi-label Linear Discriminant Analysis.

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

Proceedings of the Computer Vision - ECCV 2010, 2010

Discriminant Laplacian Embedding.

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

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

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

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

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009

Image annotation using multi-label correlated Green's function.

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

Proceedings of the IEEE 12th International Conference on Computer Vision, ICCV 2009, Kyoto, Japan, September 27, 2009