7 th Int . Conf . on Theoret . and Methodol . Issues in Mach . Trans . TMI 97 . Machine
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چکیده
Both Neural Networks and Finite-State Models have recently proved to be encouraging approaches to Example-Based Machine Translation. This paper compares the translation performances achieved with the two techniques as well as the corresponding resources required. To this end, both Elman Simple Recurrent Nets and Subsequential Transducers were trained to tackle a simple pseudo-natural machine translation task.
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Dimension-Extended Topological Relationships
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1. Aggarwal C.C. On biased reservoir sampling in the presence of stream evolution. In Proc. 32nd Int. Conf. on Very Large Data Bases, 2006. 2. Chaudhuri S. et al. Overcoming limitations of sampling for aggregation queries. In Proc. 17th Int. Conf. on Data Engineering, 2001. 3. Ganti V., Lee M.-L., and Ramakrishnan R. ICICLES: Self-tuning samples for approximate query answering. In Proc. 28th In...
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[26] A V. D. Ploeg, " Preconditioning techniques for large sparse, non-symmetric matrices with arbitrary sparsity patterns, " In Acknowledgments We would like to thank the reviewers for their valuable suggestions for improving this paper. We would also like to thank V. Vakilotojar at the University of Southern Califor-nia for many insightful discussions and comments related to this work. Algebr...
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