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07/25/2020
Adversarial Privacy-preserving Filter
While widely adopted in practical applications, face recognition has bee...
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04/22/2019
blessing in disguise: Designing Robust Turing Test by Employing Algorithm Unrobustness
Turing test was originally proposed to examine whether machine's behavio...
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07/03/2017
Vectorial Dimension Reduction for Tensors Based on Bayesian Inference
Dimensionality reduction for high-order tensors is a challenging problem...
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05/17/2017
Localized LRR on Grassmann Manifolds: An Extrinsic View
Subspace data representation has recently become a common practice in ma...
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09/21/2016
Partial Least Squares Regression on Riemannian Manifolds and Its Application in Classifications
Partial least squares regression (PLSR) has been a popular technique to ...
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09/21/2016
Matrix Variate RBM Model with Gaussian Distributions
Restricted Boltzmann Machine (RBM) is a particular type of random neural...
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06/13/2016
Laplacian LRR on Product Grassmann Manifolds for Human Activity Clustering in Multi-Camera Video Surveillance
In multi-camera video surveillance, it is challenging to represent video...
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01/21/2016
Partial Sum Minimization of Singular Values Representation on Grassmann Manifolds
As a significant subspace clustering method, low rank representation (LR...
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01/09/2016
Kernelized LRR on Grassmann Manifolds for Subspace Clustering
Low rank representation (LRR) has recently attracted great interest due ...
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01/07/2016
Block-Diagonal Sparse Representation by Learning a Linear Combination Dictionary for Recognition
In a sparse representation based recognition scheme, it is critical to l...
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01/07/2016
Mixture of Bilateral-Projection Two-dimensional Probabilistic Principal Component Analysis
The probabilistic principal component analysis (PPCA) is built upon a gl...
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01/05/2016
Matrix Variate RBM and Its Applications
Restricted Boltzmann Machine (RBM) is an importan- t generative model mo...
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01/02/2016
Tensor Sparse and Low-Rank based Submodule Clustering Method for Multi-way Data
A new submodule clustering method via sparse and low-rank representation...
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12/07/2015
Fast Optimization Algorithm on Riemannian Manifolds and Its Application in Low-Rank Representation
The paper addresses the problem of optimizing a class of composite funct...
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04/08/2015
Low Rank Representation on Grassmann Manifolds: An Extrinsic Perspective
Many computer vision algorithms employ subspace models to represent data...
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04/08/2015