List of works - Junbin Gao

A Decoder-Free Variational Deep Embedding for Unsupervised Clustering

scientific article published in 2022

A Framework of Mixed Sparse Representations for Remote Sensing Images

A Sparse Oblique-Manifold Nonnegative Matrix Factorization for Hyperspectral Unmixing

scientific article published in 2022

A novel approach in discovering significant interactions from TCM patient prescription data.

scientific article

An improved independent component analysis model for 3D chromatogram separation and its solution by multi-areas genetic algorithm.

scientific article published on 6 November 2014

An ordered-patch-based image classification approach on the image Grassmannian manifold

scientific article published in April 2014

Branched convolutional neural networks incorporated with Jacobian deep regression for facial landmark detection

scientific article published on 19 June 2019

Correlated spatio-temporal data collection in wireless sensor networks based on low rank matrix approximation and optimized node sampling.

scientific article

Deep Attention-Based Spatially Recursive Networks for Fine-Grained Visual Recognition

scientific article published on 22 March 2018

Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification

scientific article published on 02 April 2020

Domain Adaptation as Optimal Transport on Grassmann Manifolds

scientific article published in 2022

Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering.

scientific article published on 24 August 2015

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization.

scientific article published on March 2016

Hierarchical Multi-Granularity Interaction Graph Convolutional Network for Long Document Classification

scientific article published on 28 February 2024

IME: Integrating Multi-curvature Shared and Specific Embedding for Temporal Knowledge Graph Completion

scientific article published on 08 May 2024

Image Outlier Detection and Feature Extraction via L1-Norm-Based 2D Probabilistic PCA.

scientific article published on 17 August 2015

Improved Variance Reduction Methods for Riemannian Non-Convex Optimization

scientific article published in 2022

Laplacian Regularized Low-Rank Representation and Its Applications.

scientific article published on March 2016

Localized LRR on Grassmann Manifold: An Extrinsic View

scientific article published in 2018

Log-Euclidean Metrics for Contrast Preserving Decolorization.

scientific article published on 25 August 2017

Multi-Dimensional Sparse Models.

scientific article

Multiview Spectral Clustering via Structured Low-Rank Matrix Factorization

scientific article published on 04 January 2018

Multiview Subspace Clustering via Tensorial t-Product Representation

scientific article published on 27 July 2018

Nonlinear Identification Using Orthogonal Forward Regression With Nested Optimal Regularization.

scientific article published on 27 January 2015

On a class of support vector kernels based on frames in function Hilbert spaces

scientific article published on 01 September 2001

On the construction of the relevance vector machine based on Bayesian Ying-Yang harmony learning

scientific article published on 4 September 2013

Ordered Subspace Clustering With Block-Diagonal Priors

scientific article published on 26 November 2015

Parametric Classification of Bingham Distributions Based on Grassmann Manifolds

scientific article published on 24 June 2019

Probabilistic Linear Discriminant Analysis Based on L₁-Norm and Its Bayesian Variational Inference

scientific article published on 05 May 2020

Probabilistic Linear Discriminant Analysis With Vectorial Representation for Tensor Data

scientific article published on 21 March 2019

Progressive Hard-Mining Network for Monocular Depth Estimation

scientific article published in August 2018

Rank Consistency Induced Multiview Subspace Clustering via Low-Rank Matrix Factorization

scientific article published in 2022

Reflectance Prediction Modelling for Residual-Based Hyperspectral Image Coding

scientific article

Relations Among Some Low-Rank Subspace Recovery Models

scientific article published on 10 July 2015

Relevance units latent variable model and nonlinear dimensionality reduction

scientific article published on 24 November 2009

Robust Functional Manifold Clustering

scientific article published on 02 April 2020

Robust L1 principal component analysis and its Bayesian variational inference

scientific article published in February 2008

Scalable Proximal Jacobian Iteration Method With Global Convergence Analysis for Nonconvex Unconstrained Composite Optimizations

scientific article published on 15 January 2019

Sensitivity analysis applied to the construction of radial basis function networks

scientific article published in September 2005

Significant vector learning to construct sparse kernel regression models

scientific article published on 6 June 2007

Simulated maximum likelihood method for estimating kinetic rates in gene expression

scientific article published on 26 October 2006

Solving Partial Least Squares Regression via Manifold Optimization Approaches

scientific article published on 09 July 2018

Sparse Density Estimation on the Multinomial Manifold

scientific article published on 29 January 2015

Sparse kernel learning with LASSO and Bayesian inference algorithm.

scientific article published on 9 July 2009

Stock Ranking Prediction Using List-Wise Approach and Node Embedding Technique

scientific article published in 2021

Subspace Clustering via Learning an Adaptive Low-Rank Graph

scientific article published in August 2018

Supervised latent linear Gaussian process latent variable model for dimensionality reduction.

scientific article

TPSLVM: a dimensionality reduction algorithm based on thin plate splines.

scientific article published in October 2014

Tensor LRR and Sparse Coding-Based Subspace Clustering.

scientific article

TopicCAT: Unsupervised Topic-Guided Co-Attention Transformer for Extreme Multimodal Summarisation

scientific article published on 27 October 2023

UND: unite-and-divide method in Fourier and Radon domains for line segment detection.

scientific article published in June 2013

Vectorial Dimension Reduction for Tensors Based on Bayesian Inference

scientific article published on 21 November 2017

List of works by Junbin Gao

A Decoder-Free Variational Deep Embedding for Unsupervised Clustering

A Framework of Mixed Sparse Representations for Remote Sensing Images

A Sparse Oblique-Manifold Nonnegative Matrix Factorization for Hyperspectral Unmixing

A novel approach in discovering significant interactions from TCM patient prescription data.

An improved independent component analysis model for 3D chromatogram separation and its solution by multi-areas genetic algorithm.

An ordered-patch-based image classification approach on the image Grassmannian manifold

Branched convolutional neural networks incorporated with Jacobian deep regression for facial landmark detection

Correlated spatio-temporal data collection in wireless sensor networks based on low rank matrix approximation and optimized node sampling.

Deep Attention-Based Spatially Recursive Networks for Fine-Grained Visual Recognition

Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification

Domain Adaptation as Optimal Transport on Grassmann Manifolds

Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering.

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization.

Hierarchical Multi-Granularity Interaction Graph Convolutional Network for Long Document Classification

IME: Integrating Multi-curvature Shared and Specific Embedding for Temporal Knowledge Graph Completion

Image Outlier Detection and Feature Extraction via L1-Norm-Based 2D Probabilistic PCA.

Improved Variance Reduction Methods for Riemannian Non-Convex Optimization

Laplacian Regularized Low-Rank Representation and Its Applications.

Localized LRR on Grassmann Manifold: An Extrinsic View

Log-Euclidean Metrics for Contrast Preserving Decolorization.

Multi-Dimensional Sparse Models.

Multiview Spectral Clustering via Structured Low-Rank Matrix Factorization

Multiview Subspace Clustering via Tensorial t-Product Representation

Nonlinear Identification Using Orthogonal Forward Regression With Nested Optimal Regularization.

On a class of support vector kernels based on frames in function Hilbert spaces

On the construction of the relevance vector machine based on Bayesian Ying-Yang harmony learning

Ordered Subspace Clustering With Block-Diagonal Priors

Parametric Classification of Bingham Distributions Based on Grassmann Manifolds

Probabilistic Linear Discriminant Analysis Based on L₁-Norm and Its Bayesian Variational Inference

Probabilistic Linear Discriminant Analysis With Vectorial Representation for Tensor Data

Progressive Hard-Mining Network for Monocular Depth Estimation

Rank Consistency Induced Multiview Subspace Clustering via Low-Rank Matrix Factorization

Reflectance Prediction Modelling for Residual-Based Hyperspectral Image Coding

Relations Among Some Low-Rank Subspace Recovery Models

Relevance units latent variable model and nonlinear dimensionality reduction

Robust Functional Manifold Clustering

Robust L1 principal component analysis and its Bayesian variational inference

Scalable Proximal Jacobian Iteration Method With Global Convergence Analysis for Nonconvex Unconstrained Composite Optimizations

Sensitivity analysis applied to the construction of radial basis function networks

Significant vector learning to construct sparse kernel regression models

Simulated maximum likelihood method for estimating kinetic rates in gene expression

Solving Partial Least Squares Regression via Manifold Optimization Approaches

Sparse Density Estimation on the Multinomial Manifold

Sparse kernel learning with LASSO and Bayesian inference algorithm.

Stock Ranking Prediction Using List-Wise Approach and Node Embedding Technique

Subspace Clustering via Learning an Adaptive Low-Rank Graph

Supervised latent linear Gaussian process latent variable model for dimensionality reduction.

TPSLVM: a dimensionality reduction algorithm based on thin plate splines.

Tensor LRR and Sparse Coding-Based Subspace Clustering.

TopicCAT: Unsupervised Topic-Guided Co-Attention Transformer for Extreme Multimodal Summarisation

UND: unite-and-divide method in Fourier and Radon domains for line segment detection.

Vectorial Dimension Reduction for Tensors Based on Bayesian Inference