| P11-1137 | shows the performance of each | dimensionality-reduction | technique across the regularization |
| D13-1199 | therefore investigate an LDA-based | dimensionality-reduction | approach ( RLDA ) to derive effective |
| S15-2112 | Additionally , we would like to explore | dimensionality-reduction | methods like Spectral Clustering |
| D13-1199 | 4.2 ) . The effectiveness of our | dimensionality-reduction | approach will be directly evaluated |
| W09-2104 | least-squares approximation . A | dimensionality-reduction | step is performed , resulting |
| W06-1605 | the " concepts " generated by | dimensionality-reduction | methods such as latent semantic |
| W12-2004 | second-order effects in common with other | dimensionality-reduction | methods based on singular value |
