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• W1558925596 abstract "We present an online learning algorithm for training parsers which allows for the inclusion of multiple objective functions. The primary example is the extension of a standard supervised parsing objective function with additional loss-functions, either based on intrinsic parsing quality or task-specific extrinsic measures of quality. Our empirical results show how this approach performs for two dependency parsing algorithms (graph-based and transition-based parsing) and how it achieves increased performance on multiple target tasks including reordering for machine translation and parser adaptation." @default.
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• W1558925596 date "2011-07-27" @default.
• W1558925596 modified "2023-09-23" @default.
• W1558925596 title "Training dependency parsers by jointly optimizing multiple objectives" @default.
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