Jun Wang

Orcid: 0000-0002-5890-0365

Affiliations:

Shandong University, SDU-NTU Joint Centre For AI Research, C-FAIR, Jinan, China
Southwest University, College of Computer and Information Science, Chongqing, China
Harbin Institute of Technology, School of Computer Science and Technology, China (PhD 2010)

According to our database¹, Jun Wang authored at least 112 papers between 2008 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Causality-Based Fair Multiple Decision by Response Functions.

[BibT_eX]

[DOI]

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

Personalized Federated Few-Shot Learning.

[BibT_eX]

[DOI]

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

Gradient-Based Local Causal Structure Learning.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., January, 2024

Multiple clusterings: Recent advances and perspectives.

[BibT_eX]

[DOI]

Comput. Sci. Rev., 2024

Semi-Asynchronous Online Federated Crowdsourcing.

[BibT_eX]

[DOI]

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Federated Causality Learning with Explainable Adaptive Optimization.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Multi-Dimensional Fair Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Multi-Granularity Causal Structure Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Directed Acyclic Graph Learning on Attributed Heterogeneous Network.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., October, 2023

A Diversified Attention Model for Interpretable Multiple Clusterings.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., September, 2023

Meta Multi-Instance Multi-Label learning by heterogeneous network fusion.

[BibT_eX]

[DOI]

Inf. Fusion, June, 2023

Cooperative driver pathways discovery by multiplex network embedding.

[BibT_eX]

[DOI]

Briefings Bioinform., May, 2023

scMCs: a framework for single-cell multi-omics data integration and multiple clusterings.

[BibT_eX]

[DOI]

Bioinform., April, 2023

scGGAN: single-cell RNA-seq imputation by graph-based generative adversarial network.

[BibT_eX]

[DOI]

Briefings Bioinform., March, 2023

Differential Gene Expression Prediction by Ensemble Deep Networks on Histone Modification Data.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2023

Causal Discovery by Graph Attention Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Reinforcement Causal Structure Learning on Order Graph.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Incentive-Boosted Federated Crowdsourcing.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Long-Tail Cross Modal Hashing.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Lung cancer subtype diagnosis using weakly-paired multi-omics data.

[BibT_eX]

[DOI]

Bioinform., November, 2022

Multiview Multi-Instance Multilabel Active Learning.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2022

Flexible Cross-Modal Hashing.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2022

CMAL: Cost-Effective Multi-Label Active Learning by Querying Subexamples.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2022

DeepIDA: Predicting Isoform-Disease Associations by Data Fusion and Deep Neural Networks.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Tissue Specificity Based Isoform Function Prediction.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

DeepIII: Predicting Isoform-Isoform Interactions by Deep Neural Networks and Data Fusion.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

EpiMC: Detecting Epistatic Interactions Using Multiple Clusterings.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Weakly Supervised Cross-Modal Hashing.

[BibT_eX]

[DOI]

IEEE Trans. Big Data, 2022

Self-paced annotations of crowd workers.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2022

ELSSI: parallel SNP-SNP interactions detection by ensemble multi-type detectors.

[BibT_eX]

[DOI]

Briefings Bioinform., 2022

Differentially expressed genes prediction by multiple self-attention on epigenetics data.

[BibT_eX]

[DOI]

Briefings Bioinform., 2022

Phenotype Prediction by Heterogeneous Molecular Network Embedding.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021

Active Multilabel Crowd Consensus.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2021

Co-Clustering Ensembles Based on Multiple Relevance Measures.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2021

CrowdWT: Crowdsourcing via Joint Modeling of Workers and Tasks.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2021

Discovering Multiple Co-Clusterings With Matrix Factorization.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2021

Individuality- and Commonality-Based Multiview Multilabel Learning.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2021

Cross-Species Protein Function Prediction with Asynchronous-Random Walk.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2021

CDPath: Cooperative Driver Pathways Discovery Using Integer Linear Programming and Markov Clustering.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Multiple clusterings of heterogeneous information networks.

[BibT_eX]

[DOI]

Mach. Learn., 2021

IsoDA: Isoform-Disease Association Prediction by Multiomics Data Fusion.

[BibT_eX]

[DOI]

J. Comput. Biol., 2021

Imbalance deep multi-instance learning for predicting isoform-isoform interactions.

[BibT_eX]

[DOI]

Int. J. Intell. Syst., 2021

MetaMIML: Meta Multi-Instance Multi-Label Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Cooperative driver pathway discovery via fusion of multi-relational data of genes, miRNAs and pathways.

[BibT_eX]

[DOI]

Briefings Bioinform., 2021

Crowdsourcing with Self-paced Workers.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2021

Maize Epistasis Detection by Multi-class Quantitative Multifactor Dimensionality Reduction.

[BibT_eX]

[DOI]

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

Genome-Phenome Association Prediction by Deep Factorizing Heterogeneous Molecular Network.

[BibT_eX]

[DOI]

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

2020

NMFGO: Gene Function Prediction via Nonnegative Matrix Factorization with Gene Ontology.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2020

Multi-label crowd consensus via joint matrix factorization.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2020

Attributed heterogeneous network fusion via collaborative matrix tri-factorization.

[BibT_eX]

[DOI]

Inf. Fusion, 2020

Feature selection with missing labels based on label compression and local feature correlation.

[BibT_eX]

[DOI]

Neurocomputing, 2020

Predicting functions of maize proteins using graph convolutional network.

[BibT_eX]

[DOI]

BMC Bioinform., 2020

Isoform function prediction based on bi-random walks on a heterogeneous network.

[BibT_eX]

[DOI]

Bioinform., 2020

Differentiating isoform functions with collaborative matrix factorization.

[BibT_eX]

[DOI]

Bioinform., 2020

Attention-Aware Answers of the Crowd.

[BibT_eX]

[DOI]

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

EpIntMC: Detecting Epistatic Interactions Using Multiple Clusterings.

[BibT_eX]

[DOI]

Proceedings of the Bioinformatics Research and Applications - 16th International Symposium, 2020

Isoform-Disease Association Prediction by Data Fusion.

[BibT_eX]

[DOI]

Proceedings of the Bioinformatics Research and Applications - 16th International Symposium, 2020

Weakly-Supervised Multi-view Multi-instance Multi-label Learning.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Crowdsourcing with Multiple-Source Knowledge Transfer.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Partial Multi-label Learning using Label Compression.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Multi-typed Objects Multi-view Multi-instance Multi-label Learning.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Deep Incomplete Multi-View Multiple Clusterings.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Partial Multi-label Learning with Label and Feature Collaboration.

[BibT_eX]

[DOI]

Proceedings of the Database Systems for Advanced Applications, 2020

Epistasis Detection using Heterogeneous Bio-molecular Network.

[BibT_eX]

[DOI]

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

Cooperative Driver Pathway Discovery by Hierarchical Clustering and Link Prediction.

[BibT_eX]

[DOI]

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

Multi-View Multiple Clusterings Using Deep Matrix Factorization.

[BibT_eX]

[DOI]

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

2019

Protein-protein interactions prediction based on ensemble deep neural networks.

[BibT_eX]

[DOI]

Neurocomputing, 2019

Active Multi-Label Crowd Consensus.

[BibT_eX]

[DOI]

CoRR, 2019

Weakly-paired Cross-Modal Hashing.

[BibT_eX]

[DOI]

CoRR, 2019

Weighted samples based semi-supervised classification.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2019

Laplacian Eigenmaps Dimensionality Reduction Based on Clustering-Adjusted Similarity.

[BibT_eX]

[DOI]

Honghu Zhou

Jun Wang

Algorithms, 2019

CoDP: Cooperative Driver Pathways Discovery With Matrix Factorization and Tri-Random Walk.

[BibT_eX]

[DOI]

IEEE Access, 2019

Discovering Multiple Co-Clusterings in Subspaces.

[BibT_eX]

[DOI]

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

Multi-View Multiple Clustering.

[BibT_eX]

[DOI]

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

ActiveHNE: Active Heterogeneous Network Embedding.

[BibT_eX]

[DOI]

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

Cross-Modal Zero-Shot Hashing.

[BibT_eX]

[DOI]

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

Selective Matrix Factorization for Multi-relational Data Fusion.

[BibT_eX]

[DOI]

Proceedings of the Database Systems for Advanced Applications, 2019

DeepGOA: Predicting Gene Ontology Annotations of Proteins via Graph Convolutional Network.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

DMIL-III: Isoform-isoform interaction prediction using deep multi-instance learning method.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

CoPath: discovering cooperative driver pathways using greedy mutual exclusivity and bi-clustering.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Multi-View Multi-Instance Multi-Label Learning Based on Collaborative Matrix Factorization.

[BibT_eX]

[DOI]

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

Multiple Independent Subspace Clusterings.

[BibT_eX]

[DOI]

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

Ranking-Based Deep Cross-Modal Hashing.

[BibT_eX]

[DOI]

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

2018

NewGOA: Predicting New GO Annotations of Proteins by Bi-Random Walks on a Hybrid Graph.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2018

Predicting protein-protein interactions using high-quality non-interacting pairs.

[BibT_eX]

[DOI]

BMC Bioinform., 2018

BMC3C: binning metagenomic contigs using codon usage, sequence composition and read coverage.

[BibT_eX]

[DOI]

Bioinform., 2018

Matrix factorization-based data fusion for the prediction of lncRNA-disease associations.

[BibT_eX]

[DOI]

Bioinform., 2018

Multi-view Weak-label Learning based on Matrix Completion.

[BibT_eX]

[DOI]

Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Matrix Factorization for Identifying Noisy Labels of Multi-label Instances.

[BibT_eX]

[DOI]

Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 2018

Multi-Label Co-Training.

[BibT_eX]

[DOI]

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

Incomplete Multi-View Weak-Label Learning.

[BibT_eX]

[DOI]

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

Feature-Induced Partial Multi-label Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2018

Multiple Co-clusterings.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2018

Multi-label Answer Aggregation Based on Joint Matrix Factorization.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2018

Cost Effective Multi-label Active Learning via Querying Subexamples.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2018

Weighted matrix factorization based data fusion for predicting lncRNA-disease associations.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

2017

Semi-supervised multi-label classification using incomplete label information.

[BibT_eX]

[DOI]

Neurocomputing, 2017

HashGO: hashing gene ontology for protein function prediction.

[BibT_eX]

[DOI]

Comput. Biol. Chem., 2017

NoGOA: predicting noisy GO annotations using evidences and sparse representation.

[BibT_eX]

[DOI]

Guoxian Yu

Chang Lu

Jun Wang

BMC Bioinform., 2017

Semi-supervised classification by discriminative regularization.

[BibT_eX]

[DOI]

Jun Wang

Guangjun Yao

Guoxian Yu

Appl. Soft Comput., 2017

Semi-Supervised Multi-Label Dimensionality Reduction Based on Dependence Maximization.

[BibT_eX]

[DOI]

IEEE Access, 2017

2016

Predicting Protein Function via Semantic Integration of Multiple Networks.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2016

NoisyGOA: Noisy GO annotations prediction using taxonomic and semantic similarity.

[BibT_eX]

[DOI]

Comput. Biol. Chem., 2016

Interspecies gene function prediction using semantic similarity.

[BibT_eX]

[DOI]

BMC Syst. Biol., 2016

NegGOA: negative GO annotations selection using ontology structure.

[BibT_eX]

[DOI]

Bioinform., 2016

Semi-Supervised Classification Based on Low Rank Representation.

[BibT_eX]

[DOI]

Xuan Hou

Guangjun Yao

Jun Wang

Algorithms, 2016

2010

SNPs and entropy based hierarchical clustering method for genetic phylogeny analysis.

[BibT_eX]

[DOI]

Jun Wang

Maozu Guo

Proceedings of the Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010

Two-stage clustering based effective sample selection for classification of pre-miRNAs.

[BibT_eX]

[DOI]

Proceedings of the 2010 IEEE International Conference on Bioinformatics and Biomedicine, 2010

A graph and hierarchical clustering based approach for population structure inference.

[BibT_eX]

[DOI]

Jun Wang

Maozu Guo

Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology, 2010

2009

A hybrid clustering and graph based algorithm for tagSNP selection.

[BibT_eX]

[DOI]

Soft Comput., 2009

CGTS: a site-clustering graph based tagSNP selection algorithm in genotype data.

[BibT_eX]

[DOI]

Jun Wang

Maozu Guo

Chun-yu Wang

BMC Bioinform., 2009

2008

TagSNPs Selection Using Maximum Density Subgraph.

[BibT_eX]

[DOI]

Proceedings of the Fourth International Conference on Natural Computation, 2008

Jun Wang

Timeline

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