In this paper, we discuss the non-decomposability of lattices over Z[(-5)～(1/2)] All lattices of rank 2 with discriminant 2 are found and the lattices of rank n ≥3 with discriminant 2 are constructed.
While optimizing model parameters with respect to evaluation metrics has recently proven to benefit end to-end neural machine translation (NMT), the evaluation metrics used in the training are restricted to be defined...While optimizing model parameters with respect to evaluation metrics has recently proven to benefit end to-end neural machine translation (NMT), the evaluation metrics used in the training are restricted to be defined at the sentence level to facilitate online learning algorithms. This is undesirable because the final evaluation metrics used in the testing phase are usually non-decomposable (i.e., they are defined at the corpus level and cannot be expressed as the sum of sentence-level metrics). To minimize the discrepancy between the training and the testing, we propose to extend the minimum risk training (MRT) algorithm to take non-decomposable corpus-level evaluation metrics into consideration while still keeping the advantages of online training. This can be done by calculating corpus-level evaluation metrics on a subset of training data at each step in online training. Experiments on Chinese-English and English-French translation show that our approach improves the correlation between training and testing and significantly outperforms the MRT algorithm using decomposable evaluation metrics.展开更多
The minimax optimization model introduced in this paper is an important model which has received some attention over the past years. In this paper, the application of minimax model on how to select the distribution ce...The minimax optimization model introduced in this paper is an important model which has received some attention over the past years. In this paper, the application of minimax model on how to select the distribution center location is first introduced. Then a new algorithm with nonmonotone line search to solve the non-decomposable minimax optimization is proposed. We prove that the new algorithm is global Convergent. Numerical results show the proposed algorithm is effective.展开更多
文摘In this paper, we discuss the non-decomposability of lattices over Z[(-5)～(1/2)] All lattices of rank 2 with discriminant 2 are found and the lattices of rank n ≥3 with discriminant 2 are constructed.
文摘While optimizing model parameters with respect to evaluation metrics has recently proven to benefit end to-end neural machine translation (NMT), the evaluation metrics used in the training are restricted to be defined at the sentence level to facilitate online learning algorithms. This is undesirable because the final evaluation metrics used in the testing phase are usually non-decomposable (i.e., they are defined at the corpus level and cannot be expressed as the sum of sentence-level metrics). To minimize the discrepancy between the training and the testing, we propose to extend the minimum risk training (MRT) algorithm to take non-decomposable corpus-level evaluation metrics into consideration while still keeping the advantages of online training. This can be done by calculating corpus-level evaluation metrics on a subset of training data at each step in online training. Experiments on Chinese-English and English-French translation show that our approach improves the correlation between training and testing and significantly outperforms the MRT algorithm using decomposable evaluation metrics.
基金Supported by the Fundamental Research Funds for the Central Universities(2014JBM044)
文摘The minimax optimization model introduced in this paper is an important model which has received some attention over the past years. In this paper, the application of minimax model on how to select the distribution center location is first introduced. Then a new algorithm with nonmonotone line search to solve the non-decomposable minimax optimization is proposed. We prove that the new algorithm is global Convergent. Numerical results show the proposed algorithm is effective.
