Discriminative dictionary learning (DDL) aims to address pattern classification problems via
learning dictionaries from training samples. Dictionary pair learning (DPL) based DDL has …

Dictionary learning has been widely applied in the field of pattern classification. Although
many analysis-synthesis dictionary pair learning methods have been proposed in recent …

Discriminative dictionary learning (DL) has been widely studied in various pattern
classification problems. Most of the existing DL methods aim to learn a synthesis dictionary …

Discriminative dictionary learning has been extensively used for pattern classification tasks.
By incorporating different kinds of label information into the dictionary learning framework, a …

The dictionary pair learning (DPL) model aims to design a synthesis dictionary and an
analysis dictionary to accomplish the goal of rapid sample encoding. In this article, we …

Discriminative dictionary learning aims to learn a dictionary from training samples to
enhance the discriminative capability of their coding vectors. Several discrimination terms …

Dictionary learning has been widely used in the field of pattern recognition. Although the
existing synthesis dictionary learning methods have achieved impressive results, they need …

Discriminative dictionary learning (DDL) has demonstrated significantly improved
performance for image classification. However, most of the existing DDL methods just adopt …

Dictionary learning (DL) plays an important role in pattern classification. However, learning a
discriminative dictionary has not been well addressed in analysis dictionary learning (ADL) …

Discriminative dictionary learning (DDL) has attracted significant attention in the field of
image classification. To enhance the classification performance, most existing discriminative …