Guoxian Yu

Orcid: 0000-0002-1667-6705

Affiliations:

Southwest University, Beibei, Chongqing, China

According to our database¹, Guoxian Yu authored at least 164 papers between 2011 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

Few-shot partial multi-label learning with synthetic features network.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., February, 2024

Gradient-Based Local Causal Structure Learning.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., January, 2024

FedTA: Federated Worthy Task Assignment for Crowd Workers.

[BibT_eX]

[DOI]

IEEE Trans. Dependable Secur. Comput., 2024

Multiple clusterings: Recent advances and perspectives.

[BibT_eX]

[DOI]

Comput. Sci. Rev., 2024

Calibration-compatible Listwise Distillation of Privileged Features for CTR Prediction.

[BibT_eX]

[DOI]

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 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

Few-shot partial multi-label learning via prototype rectification.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., April, 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

Lung Cancer Subtype Diagnosis by Fusing Image-Genomics Data and Hybrid Deep Networks.

[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

Entire Space Cascade Delayed Feedback Modeling for Effective Conversion Rate Prediction.

[BibT_eX]

[DOI]

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 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

Isoform function prediction by Gene Ontology embedding.

[BibT_eX]

[DOI]

Bioinform., 2022

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

[BibT_eX]

[DOI]

Briefings Bioinform., 2022

Graph Alignment with Noisy Supervision.

[BibT_eX]

[DOI]

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Few-shot Partial Multi-label Learning with Data Augmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 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

Dual self-paced multi-view clustering.

[BibT_eX]

[DOI]

Neural Networks, 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

Noise-robust Deep Cross-Modal Hashing.

[BibT_eX]

[DOI]

Inf. Sci., 2021

Cost-effective Batch-mode Multi-label Active Learning.

[BibT_eX]

[DOI]

Xiaoqiang Gui

Xudong Lu

Guoxian Yu

Neurocomputing, 2021

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

[BibT_eX]

[DOI]

Int. J. Intell. Syst., 2021

Cost-effective multi-instance multilabel active learning.

[BibT_eX]

[DOI]

Cong Su

Zhongmin Yan

Guoxian Yu

Int. J. Intell. Syst., 2021

Large-scale online multi-view graph neural network and applications.

[BibT_eX]

[DOI]

Future Gener. Comput. Syst., 2021

MetaMIML: Meta Multi-Instance Multi-Label Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Meta Cross-Modal Hashing on Long-Tailed Data.

[BibT_eX]

[DOI]

CoRR, 2021

Cross-modal Zero-shot Hashing by Label Attributes Embedding.

[BibT_eX]

[DOI]

CoRR, 2021

Open-Set Crowdsourcing using Multiple-Source Transfer Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Crowdsourcing with Meta-Workers: A New Way to Save the Budget.

[BibT_eX]

[DOI]

CoRR, 2021

DMIL-IsoFun: predicting isoform function using deep multi-instance learning.

[BibT_eX]

[DOI]

Bioinform., 2021

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

[BibT_eX]

[DOI]

Briefings Bioinform., 2021

Deep Multi-type Objects Muli-view Multi-instance Multi-label Learning.

[BibT_eX]

[DOI]

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Few-Shot Partial-Label Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Few-Shot Partial Multi-Label Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2021

Incomplete Multi-view Multi-label Active Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 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 zero-shot learning with graph convolutional networks.

[BibT_eX]

[DOI]

Neural Networks, 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

REA: Robust Cross-lingual Entity Alignment Between Knowledge Graphs.

[BibT_eX]

[DOI]

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and 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

Link Inference via Heterogeneous Multi-view Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Database Systems for Advanced Applications, 2020

Dynamical User Intention Prediction via Multi-modal Learning.

[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

CLUE: Personalized Hospital Readmission Prediction Against Data Insufficiency under Imbalanced-Data Environment.

[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

Drug repositioning based on individual bi-random walks on a heterogeneous network.

[BibT_eX]

[DOI]

BMC Bioinform., December, 2019

SHOAL: Large-scale Hierarchical Taxonomy via Graph-based Query Coalition in E-commerce.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2019

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

[BibT_eX]

[DOI]

Neurocomputing, 2019

Prototypical Networks for Multi-Label Learning.

[BibT_eX]

[DOI]

CoRR, 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

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

Affinity Propagation Clustering Using Centroid-Deviation-Distance Based Similarity.

[BibT_eX]

[DOI]

Proceedings of the Human Brain and Artificial Intelligence - First International Workshop, 2019

Consistent and Specific Multi-view Relative-Transform Classification.

[BibT_eX]

[DOI]

Proceedings of the Human Brain and Artificial Intelligence - First International Workshop, 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

Semi-supervised DenPeak Clustering with Pairwise Constraints.

[BibT_eX]

[DOI]

Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 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

Multi-Label Classification Based on Low Rank Representation for Image Annotation.

[BibT_eX]

[DOI]

Remote. Sens., 2017

Weighted-object ensemble clustering: methods and analysis.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 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

Semi-supervised Multi-label Linear Discriminant Analysis.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing - 24th International Conference, 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

Affinity Propagation Clustering Using Path Based Similarity.

[BibT_eX]

[DOI]

Yuan Jiang

Yuliang Liao

Guoxian Yu

Algorithms, 2016

2015

Predicting Protein Function Using Multiple Kernels.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2015

Semi-supervised classification based on subspace sparse representation.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2015

Integrating multiple networks for protein function prediction.

[BibT_eX]

[DOI]

BMC Syst. Biol., 2015

Predicting protein function via downward random walks on a gene ontology.

[BibT_eX]

[DOI]

BMC Bioinform., 2015

Predicting protein functions using incomplete hierarchical labels.

[BibT_eX]

[DOI]

Guo-Xian Yu

Hailong Zhu

Carlotta Domeniconi

BMC Bioinform., 2015

Semi-Supervised Classification Based on Mixture Graph.

[BibT_eX]

[DOI]

Lei Feng

Guoxian Yu

Algorithms, 2015

2014

Protein Function Prediction withIncomplete Annotations.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2014

Erratum to "Protein Function Prediction Using Multilabel Ensemble Classification".

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2014

Probabilistic cluster structure ensemble.

[BibT_eX]

[DOI]

Inf. Sci., 2014

A Weighted Adaptive Mean Shift Clustering Algorithm.

[BibT_eX]

[DOI]

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

2013

Protein Function Prediction Using Multilabel Ensemble Classification.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2013

Hidden Markov Models for Real-Time Estimation of Corn Progress Stages Using MODIS and Meteorological Data.

[BibT_eX]

[DOI]

Remote. Sens., 2013

Protein Function Prediction Using Dependence Maximization.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Protein Function Prediction by Integrating Multiple Kernels.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2013, 2013

Exploiting neighbors' latent correlation for link prediction in complex network.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Cybernetics, 2013

Weighted-Object Ensemble Clustering.

[BibT_eX]

[DOI]

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012

Semi-supervised classification based on random subspace dimensionality reduction.

[BibT_eX]

[DOI]

Pattern Recognit., 2012

Hybrid cluster ensemble framework based on the random combination of data transformation operators.

[BibT_eX]

[DOI]

Pattern Recognit., 2012

Local and global structure preserving based feature selection.

[BibT_eX]

[DOI]

Neurocomputing, 2012

Semi-supervised ensemble classification in subspaces.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2012

Transductive multi-label ensemble classification for protein function prediction.

[BibT_eX]

[DOI]

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Protein function prediction using weak-label learning.

[BibT_eX]

[DOI]

Proceedings of the ACM International Conference on Bioinformatics, 2012

2011

Enhanced locality preserving projections using robust path based similarity.

[BibT_eX]

[DOI]

Neurocomputing, 2011

Sparse representation based spectral regression.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Cybernetics, 2011

Random subspace based semi-supervised feature selection.

[BibT_eX]

[DOI]

Ya-Zhou Ren

Guoji Zhang

Guo-Xian Yu

Proceedings of the International Conference on Machine Learning and Cybernetics, 2011

Guoxian Yu

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