TY - GEN
T1 - Dictionary learning based on laplacian score in sparse coding
AU - Xu, Jin
AU - Man, Hong
PY - 2011
Y1 - 2011
N2 - Sparse coding, which produces a vector representation based on sparse linear combination of dictionary atoms, has been widely applied in signal processing, data mining and neuroscience. Constructing a proper dictionary for sparse coding is a common challenging problem. In this paper, we treat dictionary learning as an unsupervised learning process, and propose a Laplacian score dictionary (LSD). This new learning method uses local geometry information to select atoms for the dictionary. Comparisons with alternative clustering based dictionary learning methods are conducted. We also compare LSD with full-training-data-dictionary and others classic methods in the experiments. The classification performances on binary-class datasets and multi-class datasets from UCI repository demonstrate the effectiveness and efficiency of our method.
AB - Sparse coding, which produces a vector representation based on sparse linear combination of dictionary atoms, has been widely applied in signal processing, data mining and neuroscience. Constructing a proper dictionary for sparse coding is a common challenging problem. In this paper, we treat dictionary learning as an unsupervised learning process, and propose a Laplacian score dictionary (LSD). This new learning method uses local geometry information to select atoms for the dictionary. Comparisons with alternative clustering based dictionary learning methods are conducted. We also compare LSD with full-training-data-dictionary and others classic methods in the experiments. The classification performances on binary-class datasets and multi-class datasets from UCI repository demonstrate the effectiveness and efficiency of our method.
KW - Clustering
KW - Dictionary learning
KW - Laplacian Score
KW - Sparse coding
KW - Unsupervised learning
UR - http://www.scopus.com/inward/record.url?scp=80052311298&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80052311298&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-23199-5_19
DO - 10.1007/978-3-642-23199-5_19
M3 - Conference contribution
AN - SCOPUS:80052311298
SN - 9783642231988
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 253
EP - 264
BT - Machine Learning and Data Mining in Pattern Recognition - 7th International Conference, MLDM 2011, Proceedings
T2 - 7th International Conference on Machine Learning and Data Mining, MLDM 2011
Y2 - 30 August 2011 through 3 September 2011
ER -