TY  - CONF
AU  - Katerine Diaz
AU  - Francesc J. Ferri
AU  - W. Diaz
A2  - ICONIP
PY  - 2013//
TI  - Fast Approximated Discriminative Common Vectors using rank-one SVD updates
T2  - LNCS
BT  - 20th International Conference On Neural Information Processing
SP  - 368
EP  - 375
VL  - 8228
IS  - III
PB  - Springer Berlin Heidelberg
N2  - An efficient incremental approach to the discriminative common vector (DCV) method for dimensionality reduction and classification is presented. The proposal consists of a rank-one update along with an adaptive restriction on the rank of the null space which leads to an approximate but convenient solution. The algorithm can be implemented very efficiently in terms of matrix operations and space complexity, which enables its use in large-scale dynamic application domains. Deep comparative experimentation using publicly available high dimensional image datasets has been carried out in order to properly assess the proposed algorithm against several recent incremental formulations.K. Diaz-Chito,  F.J. Ferri, W. Diaz
SN  - 0302-9743
SN  - 978-3-642-42050-4
UR  - http://dx.doi.org/10.1007/978-3-642-42051-1_46
N1  - ADAS
ID  - Katerine Diaz2013
ER  -