6 papers
Automatic Subspace Learning via Principal Coefficients Embedding
Xi Peng, Jiwen Lu, Zhang Yi +1
In this paper, we address two challenging problems in unsupervised subspace learning: 1) how to automatically identify the feature dimension of the learned subspace (i.e., automati…
Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification
Xi Peng, Rui Yan, Bo Zhao +2
Spatial Pyramid Matching (SPM) and its variants have achieved a lot of success in image classification. The main difference among them is their encoding schemes. For example, ScSPM…
A Unified Framework for Representation-based Subspace Clustering of Out-of-sample and Large-scale Data
Xi Peng, Huajin Tang, Lei Zhang +2
Under the framework of spectral clustering, the key of subspace clustering is building a similarity graph which describes the neighborhood relations among data points. Some recent…
Inductive Sparse Subspace Clustering
Xi Peng, Lei Zhang, Zhang Yi
Sparse Subspace Clustering (SSC) has achieved state-of-the-art clustering quality by performing spectral clustering over a -norm based similarity graph. However, SSC is a…
Learning Locality-Constrained Collaborative Representation for Face Recognition
Xi Peng, Lei Zhang, Zhang Yi +1
The model of low-dimensional manifold and sparse representation are two well-known concise models that suggest each data can be described by a few characteristics. Manifold learnin…
Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering
Xi Peng, Zhiding Yu, Huajin Tang +1
Under the framework of graph-based learning, the key to robust subspace clustering and subspace learning is to obtain a good similarity graph that eliminates the effects of errors…