Dictionary Learning

Demosaicking based on Channel-Correlation Adaptive Dictionary Learning

We propose a channel-correlation adaptive dictionary learning based demosaicking (CADLD).

Dictionary Learning with Structured Noise

We propose a novel dictionary learning with structured noise (DLSN) method for handling noisy data. We decompose the original data into three parts: clean data, structured noise, and Gaussian noise, and then characterize them separately.

Joint Dictionary Learning and Semantic Constrained Latent Subspace Projection for Cross-Modal Retrieval

We present a novel joint dictionary learning and semantic constrained latent subspace learning method for cross-modal retrieval (JDSLC).

Bilevel Model Based Discriminative Dictionary Learning for Recognition

We present a novel bilevel model-based discriminative dictionary learning method for recognition tasks.

Tensor LRR and Sparse Coding Based Subspace Clustering

We propose a tensor low-rank representation (TLRR) and sparse coding-based (TLRRSC) subspace clustering method by simultaneously considering feature information and spatial structures.

Robust Subspace Segmentation by Low-Rank Representation

In this work we propose the low-rank representation (LRR) to recover the lowest-rank representation of a set of data vectors in a joint way, i.e., to recover the lowest-rank representation of matrix data.