@inproceedings{45b0eb6aeb1e4178ae0a2947a942c799,
title = "Discriminative orthonormal dictionary learning for fast low-rank representation",
abstract = "This paper presents a discriminative orthonormal dictionary learning method for low-rank representation. The orthonormal property is beneficial for the representative power of the dictionary by avoiding the dictionary redundancy. To enhance the discriminative power of the dictionary, all the class-specific dictionaries which are encouraged to well represent the samples from the same class are optimized simultaneously. With the learned discriminative orthonormal dictionary, the low-rank representation problem can be solved much faster than traditional methods. Experiments on three public datasets demonstrate the effectiveness and efficiency of our method.",
keywords = "Discriminative dictionary learning, Fast low-rank representation, Orthonormal",
author = "Zhen Dong and Mingtao Pei and Yunde Jia",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 22nd International Conference on Neural Information Processing, ICONIP 2015 ; Conference date: 09-11-2015 Through 12-11-2015",
year = "2015",
doi = "10.1007/978-3-319-26532-2\_10",
language = "English",
isbn = "9783319265315",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "79--89",
editor = "Lai, \{Weng Kin\} and Qingshan Liu and Tingwen Huang and Sabri Arik",
booktitle = "Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings",
address = "Germany",
}