TY - GEN
T1 - An efficient augmented Lagrangian algorithm for graph regularized sparse coding in clustering
AU - Liu, Qiegen
AU - Ying, Leslie
AU - Liang, Dong
PY - 2013/10/18
Y1 - 2013/10/18
N2 - The combination of sparse coding and manifold learning has received much attention recently. However, the computational complexity of the resulting optimization problem hinders its practical application. In this paper, an augmented Lagrangian method is proposed to address this issue, which first transforms the unconstrained problem to an equivalent constrained problem and then an alternating direction method is used to iteratively solve the subproblems. Experimental results validate the effectiveness of the propose algorithm.
AB - The combination of sparse coding and manifold learning has received much attention recently. However, the computational complexity of the resulting optimization problem hinders its practical application. In this paper, an augmented Lagrangian method is proposed to address this issue, which first transforms the unconstrained problem to an equivalent constrained problem and then an alternating direction method is used to iteratively solve the subproblems. Experimental results validate the effectiveness of the propose algorithm.
KW - alternating direction method
KW - augmented Lagrangian
KW - graph regularized sparse coding
KW - Image clustering
UR - https://www.scopus.com/pages/publications/84890541094
U2 - 10.1109/ICASSP.2013.6637933
DO - 10.1109/ICASSP.2013.6637933
M3 - Conference contribution
AN - SCOPUS:84890541094
SN - 9781479903566
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 1656
EP - 1660
BT - 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
T2 - 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Y2 - 26 May 2013 through 31 May 2013
ER -