Chenping Hou

According to our database1, Chenping Hou authored at least 88 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Constrained clustering with weak label prior.
Frontiers Comput. Sci., June, 2024

Absent Multiview Semisupervised Classification.
IEEE Trans. Cybern., March, 2024

Feature incremental learning with causality.
Pattern Recognit., February, 2024

Compound Weakly Supervised Clustering.
IEEE Trans. Image Process., 2024

2023
Online Learning With Incremental Feature Space and Bandit Feedback.
IEEE Trans. Knowl. Data Eng., December, 2023

Incremental Learning for Simultaneous Augmentation of Feature and Class.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Imbalanced Clustering With Theoretical Learning Bounds.
IEEE Trans. Knowl. Data Eng., September, 2023

Decorrelated spectral regression: An unsupervised dimension reduction method under data selection bias.
Neurocomputing, September, 2023

SS-TBN: A Semi-Supervised Tri-Branch Network for COVID-19 Screening and Lesion Segmentation.
IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

Adaptive Feature Selection With Augmented Attributes.
IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

Active label distribution learning via kernel maximum mean discrepancy.
Frontiers Comput. Sci., August, 2023

Semi-Supervised Learning With Label Proportion.
IEEE Trans. Knowl. Data Eng., 2023

Incomplete Multi-View Learning Under Label Shift.
IEEE Trans. Image Process., 2023

Label Distribution Changing Learning with Sample Space Expanding.
J. Mach. Learn. Res., 2023

2022
Joint Representation Learning and Clustering: A Framework for Grouping Partial Multiview Data.
IEEE Trans. Knowl. Data Eng., 2022

Incremental Feature Spaces Learning with Label Scarcity.
ACM Trans. Knowl. Discov. Data, 2022

Safe incomplete label distribution learning.
Pattern Recognit., 2022

Multi-instance positive and unlabeled learning with bi-level embedding.
Intell. Data Anal., 2022

A Novel Adaptive Causal Sampling Method for Physics-Informed Neural Networks.
CoRR, 2022

Deep Learning for Visual Speech Analysis: A Survey.
CoRR, 2022

2021
Fragmentary Multi-Instance Classification.
IEEE Trans. Cybern., 2021

Joint Embedding Learning and Low-Rank Approximation: A Framework for Incomplete Multiview Learning.
IEEE Trans. Cybern., 2021

Fragmentary label distribution learning via graph regularized maximum entropy criteria.
Pattern Recognit. Lett., 2021

Incomplete multi-view learning via half-quadratic minimization.
Neurocomputing, 2021

Active label distribution learning.
Neurocomputing, 2021

Multiple Instance Learning for Unilateral Data.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

2020
Latent Complete Row Space Recovery for Multi-View Subspace Clustering.
IEEE Trans. Image Process., 2020

Multiview Classification With Cohesion and Diversity.
IEEE Trans. Cybern., 2020

Multi-view subspace learning via bidirectional sparsity.
Pattern Recognit., 2020

Joint consensus and diversity for multi-view semi-supervised classification.
Mach. Learn., 2020

Semi-supervised multi-label feature learning via label enlarged discriminant analysis.
Knowl. Inf. Syst., 2020

Randomized multi-label subproblems concatenation via error correcting output codes.
Neurocomputing, 2020

Multi-View Spectral Clustering With Incomplete Graphs.
IEEE Access, 2020

Optimal Representative Distribution Margin Machine for Multi-Instance Learning.
IEEE Access, 2020

2019
Full Representation Data Embedding via Nonoverlapping Historical Features.
IEEE Trans. Cybern., 2019

Dimension Reduction for Non-Gaussian Data by Adaptive Discriminative Analysis.
IEEE Trans. Cybern., 2019

Safe Classification with Augmented Features.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Active learning with error-correcting output codes.
Neurocomputing, 2019

Co-learning binary classifiers for LP-based multi-label classification.
Cogn. Syst. Res., 2019

Recursive Maximum Margin Active Learning.
IEEE Access, 2019

Multi-label Active Learning with Error Correcting Output Codes.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Simultaneous Representation Learning and Clustering for Incomplete Multi-view Data.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Learning Compact Partial Differential Equations for Color Images with Efficiency.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Semi-Supervised Feature Selection via Insensitive Sparse Regression with Application to Video Semantic Recognition.
IEEE Trans. Knowl. Data Eng., 2018

One-Pass Learning with Incremental and Decremental Features.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Learning sparse partial differential equations for vector-valued images.
Neural Comput. Appl., 2018

Robust feature selection via simultaneous sapped norm and sparse regularizer minimization.
Neurocomputing, 2018

Partial multi-view spectral clustering.
Neurocomputing, 2018

Joint Embedding Learning and Low-Rank Approximation: A Framework for Incomplete Multi-view Learning.
CoRR, 2018

Incomplete Multi-view Clustering via Structured Graph Learning.
Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 2018

Similarity-Adaptive Latent Low-Rank Representation for Robust Data Representation.
Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 2018

Co-learning Binary Classifiers for LP-Based Multi-label Classification.
Proceedings of the Intelligence Science and Big Data Engineering, 2018

Low Rank Multi-Label Classification with Missing Labels.
Proceedings of the 24th International Conference on Pattern Recognition, 2018

Reliable Multi-View Clustering.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Unsupervised Single and Multiple Views Feature Extraction with Structured Graph.
IEEE Trans. Knowl. Data Eng., 2017

Multi-View Unsupervised Feature Selection with Adaptive Similarity and View Weight.
IEEE Trans. Knowl. Data Eng., 2017

Scalable Multi-View Semi-Supervised Classification via Adaptive Regression.
IEEE Trans. Image Process., 2017

2D Feature Selection by Sparse Matrix Regression.
IEEE Trans. Image Process., 2017

Secure Classification With Augmented Features.
CoRR, 2017

Multi-view Clustering with Adaptively Learned Graph.
Proceedings of The 9th Asian Conference on Machine Learning, 2017

2016
Effective Discriminative Feature Selection With Nontrivial Solution.
IEEE Trans. Neural Networks Learn. Syst., 2016

Discriminative orthogonal elastic preserving projections for classification.
Neurocomputing, 2016

Unsupervised feature extraction using a learned graph with clustering structure.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Semi-Supervised Multi-label Dimensionality Reduction.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Discriminative Vanishing Component Analysis.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Discriminative Embedded Clustering: A Framework for Grouping High-Dimensional Data.
IEEE Trans. Neural Networks Learn. Syst., 2015

Effective Discriminative Feature Selection with Non-trivial Solutions.
CoRR, 2015

2014
Joint Embedding Learning and Sparse Regression: A Framework for Unsupervised Feature Selection.
IEEE Trans. Cybern., 2014

Multiple rank multi-linear SVM for matrix data classification.
Pattern Recognit., 2014

Learning high-dimensional correspondence via manifold learning and local approximation.
Neural Comput. Appl., 2014

2013
Efficient Image Classification via Multiple Rank Regression.
IEEE Trans. Image Process., 2013

An Adaptive Approach to Learning Optimal Neighborhood Kernels.
IEEE Trans. Cybern., 2013

Robust non-negative matrix factorization via joint sparse and graph regularization for transfer learning.
Neural Comput. Appl., 2013

Learning a subspace for clustering via pattern shrinking.
Inf. Process. Manag., 2013

Robust non-negative matrix factorization via joint sparse and graph regularization.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2012
Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction.
Pattern Recognit. Lett., 2012

A general framework for transfer sparse subspace learning.
Neural Comput. Appl., 2012

Unsupervised maximum margin feature selection via L 2, 1-norm minimization.
Neural Comput. Appl., 2012

2011
Semisupervised Learning Using Negative Labels.
IEEE Trans. Neural Networks, 2011

Uncovering Community Structure in Social Networks by Clique Correlation.
Proceedings of the Modeling Decision for Artificial Intelligence, 2011

Semi-supervised Dimensionality Reduction via Harmonic Functions.
Proceedings of the Modeling Decision for Artificial Intelligence, 2011

Feature Selection via Joint Embedding Learning and Sparse Regression.
Proceedings of the IJCAI 2011, 2011

GM-transfer: Graph-based model for transfer learning.
Proceedings of the First Asian Conference on Pattern Recognition, 2011

2010
Multiple view semi-supervised dimensionality reduction.
Pattern Recognit., 2010

2009
Learning an Orthogonal and Smooth Subspace for Image Classification.
IEEE Signal Process. Lett., 2009

Stable local dimensionality reduction approaches.
Pattern Recognit., 2009

Soft Constraint Harmonic Energy Minimization for Transductive Learning and its Two Interpretations.
Neural Process. Lett., 2009

Local linear transformation embedding.
Neurocomputing, 2009


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