| Cross-Language Structural Correspondence Learning | UZVT = SVD (W) |
| Cross-Language Structural Correspondence Learning | COMPUTESVD(W, k) UZVT = SVD (W) |
| Cross-Language Structural Correspondence Learning | By computing SVD (W) one obtains a compact representation of this column space in the form of an orthonormal basis 6T. |
| Experiments | The computational bottleneck of CL-SCL is the SVD of the dense parameter matrix W. Here we follow Blitzer et al. |
| Experiments | For the SVD computation the Lanczos algorithm provided by SVDLIBC is employed.4 We investigated an alternative approach to obtain a sparse W by directly enforcing sparse pivot predictors w; through Ll-regularization (Tsuruoka et al., 2009), but didn’t pursue this strategy due to unstable results. |
| Experiments | Obviously the SVD is crucial to the success of CL-SCL if m is sufficiently large. |
| Algorithm Analysis | Moreover, algorithms which use operations such as the SVD have a limit to the corpora sizes they |
| The S-Space Framework | The S-Space Package supports two common techniques: the Singular Value Decomposition ( SVD ) and randomized projections. |
| The S-Space Framework | All matrix data structures are designed to seamlessly integrate with six SVD implementations for maximum portability, including SVDLIBJ1 , a Java port of SVDLIBCZ, a scalable sparse SVD library. |