| P97-1021 | parse , Bod ( 1993a ) gives a | Monte Carlo approximation | al - gorithm . Sima'an ( 1995 |
| E97-1021 | parse , Bod ( 1993a ) gives a | Monte Carlo approximation | al - gorithm . Sima'an ( 1995 |
| D15-1097 | log linear model and sequential | Monte Carlo approximation | . We propose an unsupervised |
| P10-1107 | exactly , we resort to the standard | Monte Carlo approximation | . We collect samples of the variables |
| W15-1602 | Monte Carlo Entropy ( MCE ) uses a | Monte Carlo approximation | to compute the entropy , i.e. |
| P13-1150 | observation type-counts Nt . 4.1 | Monte Carlo Approximation | Our goal in inference is to predict |
| D13-1007 | expectation using a nonsequential | Monte Carlo approximation | , assuming we can draw s ` , |
| W12-5206 | from the set of all parses -- | Monte Carlo approximations | -- to reduce the difficulty of |
| W96-0111 | and Rajman ( 1995a , b ) give | Monte Carlo approximation | algorithms . Sima'an ( 1995 ) |
| D13-1007 | accuracy and speed . 4.1 Sequential | Monte Carlo approximation | Sequential Monte Carlo algorithms |
| D13-1007 | gradients . 5.3 Parameters The | Monte Carlo approximations | require two pa - rameters : the |
| P13-1150 | allows us to perform the standard | Monte Carlo approximation | : f ( tw , ℓ = t | w , |
| D13-1007 | Equation 10 ) . The theory of | Monte Carlo approximation | states that the quality of the |
| P08-1075 | handle longer ones . A simple | Monte Carlo approximation | to ( 4 ) would involve sampling |
