| P04-1064 | setting . Table 4 shows that the | matrix factorisation | approach does not offer any quantitative |
| W15-1205 | et al. , 2014 ) . This is uses | matrix factorisation | on a word-context matrix which |
| W15-1803 | machine reading , using ideas from | matrix factorisation | as well as both closed and open |
| W15-1800 | machine reading , using ideas from | matrix factorisation | as well as both closed and open |
| D14-1111 | weighting scheme and nonnegative | matrix factorisation | ( NMF ) ( Grefenstette et al. |
| P04-1064 | systematic evaluation of the use of | matrix factorisation | for aligning words , we tested |
| P04-1064 | . <title> Aligning words using | matrix factorisation | </title> Cyril Goutte Kenji Yamada |
| P04-1064 | reference data : onal non-negative | matrix factorisation | ( ONMF ) using the AIC and BIC |
| P04-1064 | is an instance of non-negative | matrix factorisation | , aka NMF ( Lee and Seung , 1999 |
| P04-1064 | depends on the way M is non-negative | matrix factorisation | ( ONMF ) using the AIC and BIC |
| E14-1025 | ) . We also tried non-negative | matrix factorisation | ( NNMF ) ( Seung and Lee , 2001 |
| P04-1064 | algorithm for Orthogonal Non-negative | Matrix Factorisation | Standard NMF algorithms ( Lee |
| P09-3012 | ( 2008 ) . They use symmetric | matrix factorisation | to group similar sentences together |
| P04-1064 | perform the Orthogonal Non-negative | Matrix Factorisation | ( ONMF ) in two stages : We first |
| P04-1064 | source and target sentences . 3 | Matrix factorisation | Alignments between source and |
| W13-3913 | matrix Va. . 2.4 . Non-negative | matrix factorisation | NMF uses non-negativity constraints |
