| tech,13-6-H01-1058,ak | behavior of the <term> oracle </term> using a <term> | neural network | </term> or a <term> decision tree </term> . The | #1165 We suggest a method that mimics the behavior of the oracle using aneural network or a decision tree. | |
| tech,17-6-H01-1058,ak | using a <term> neural network </term> or a <term> | decision tree | </term> . The method amounts to tagging <term> | #1169 We suggest a method that mimics the behavior of the oracle using a neural network or adecision tree. | |
| tech,24-2-H01-1058,ak | of the <term> performance </term> of an <term> | oracle | </term> . The <term> oracle </term> knows the | #1068 We find that simple interpolation methods, like log-linear and linear interpolation, improve the performance but fall short of the performance of anoracle. | |
| tech,3-4-H01-1058,ak | different <term> LM </term> . Actually , the <term> | oracle | </term> acts like a <term> dynamic combiner | #1118 Actually, theoracle acts like a dynamic combiner with hard decisions using the reference. | |
| tech,4-2-H01-1058,ak | LMs ) </term> . We find that simple <term> | interpolation methods | </term> , like <term> log-linear and linear | #1048 We find that simpleinterpolation methods, like log-linear and linear interpolation, improve the performance but fall short of the performance of an oracle. | |
| tech,7-4-H01-1058,ak | the <term> oracle </term> acts like a <term> | dynamic combiner | </term> with hard decisions using the <term> | #1122 Actually, the oracle acts like adynamic combiner with hard decisions using the reference. | |
| tech,8-2-H01-1058,ak | interpolation methods </term> , like <term> | log-linear and linear interpolation | </term> , improve the <term> performance </term> | #1052 We find that simple interpolation methods, likelog-linear and linear interpolation, improve the performance but fall short of the performance of an oracle. |
