作者: Meager 時間: 2025-3-21 23:45
Jiaxin Zhai,Zhengtao Yu,Shengxiang Gao,Zhenhan Wang,Liuqing Pud linear programming problems, his initial model was a class of resource - location problems to be solved for the U.S. Air Force. The decisions about theallocationswerecalled‘Programs’bytheAirForce,andhencethet978-1-4614-2455-0978-0-387-79148-7Series ISSN 0172-6056 Series E-ISSN 2197-5604 作者: 輕觸 時間: 2025-3-22 00:36
Yulin Zhang,Chong Feng,Hongzheng Lid linear programming problems, his initial model was a class of resource - location problems to be solved for the U.S. Air Force. The decisions about theallocationswerecalled‘Programs’bytheAirForce,andhencethet978-1-4614-2455-0978-0-387-79148-7Series ISSN 0172-6056 Series E-ISSN 2197-5604 作者: Dislocation 時間: 2025-3-22 06:37
Independent Fusion of Words and Image for Multimodal Machine Translation,h-German sentence pairs of the multimodal machine translation dataset, Multi30k, and the Indonesian-Chinese sentence pairs which is manually annotated by human. Compared with the existing MNMT model based on RNN, our model has a better performance and proves the effectiveness of it.作者: 起草 時間: 2025-3-22 10:08 作者: fetter 時間: 2025-3-22 15:29
oped the stochastic linear programming approach, but this too has its limitations. Recently, interest has been given to linear programming problems with data given as intervals, convex sets and/or fuzzy sets. The individual results of these studies have been promising, but the 978-1-4419-4094-0978-0-387-32698-6作者: 杠桿支點 時間: 2025-3-22 18:58
Wenhao Zhu,Zhihao Zhou,Shujian Huang,Zhenya Lin,Xiangsheng Zhou,Yaofeng Tu,Jiajun Chentorical artifact. When Dantzig ?rstdevelopedthe Simplex Algorithm to solvewhat arenowcalled linear programming problems, his initial model was a class of resource - location problems to be solved for the U.S. Air Force. The decisions about theallocationswerecalled‘Programs’bytheAirForce,andhencethet作者: 騙子 時間: 2025-3-22 21:36 作者: 動物 時間: 2025-3-23 02:27
Na Ye,Yuanyuan Wang,Dongfeng Caitorical artifact. When Dantzig ?rstdevelopedthe Simplex Algorithm to solvewhat arenowcalled linear programming problems, his initial model was a class of resource - location problems to be solved for the U.S. Air Force. The decisions about theallocationswerecalled‘Programs’bytheAirForce,andhencethet作者: 產(chǎn)生 時間: 2025-3-23 07:29
Junteng Ma,Shihao Qin,Minping Chen,Xia Litorical artifact. When Dantzig ?rstdevelopedthe Simplex Algorithm to solvewhat arenowcalled linear programming problems, his initial model was a class of resource - location problems to be solved for the U.S. Air Force. The decisions about theallocationswerecalled‘Programs’bytheAirForce,andhencethet作者: bile648 時間: 2025-3-23 12:28
Ru Peng,Zhitao Chen,Tianyong Hao,Yi Fangtorical artifact. When Dantzig ?rstdevelopedthe Simplex Algorithm to solvewhat arenowcalled linear programming problems, his initial model was a class of resource - location problems to be solved for the U.S. Air Force. The decisions about theallocationswerecalled‘Programs’bytheAirForce,andhencethet作者: 愛得痛了 時間: 2025-3-23 15:50 作者: senile-dementia 時間: 2025-3-23 21:46 作者: 大包裹 時間: 2025-3-24 01:23 作者: tympanometry 時間: 2025-3-24 05:41 作者: Occupation 時間: 2025-3-24 08:36
Wenhao Zhu,Zhihao Zhou,Shujian Huang,Zhenya Lin,Xiangsheng Zhou,Yaofeng Tu,Jiajun Chennally been called Linear Programming.Theword programming in this context can be confusing and/or misleading to students. Linear programming problems are referred to as optimization problems but the general term linear p- gramming remains. This can cause people unfamiliar with the subject to think th作者: headlong 時間: 2025-3-24 11:34 作者: 用樹皮 時間: 2025-3-24 16:14 作者: RENIN 時間: 2025-3-24 19:33 作者: 我要沮喪 時間: 2025-3-25 02:41
Ru Peng,Zhitao Chen,Tianyong Hao,Yi Fangnally been called Linear Programming.Theword programming in this context can be confusing and/or misleading to students. Linear programming problems are referred to as optimization problems but the general term linear p- gramming remains. This can cause people unfamiliar with the subject to think th作者: Microaneurysm 時間: 2025-3-25 06:55
Jiaxin Zhai,Zhengtao Yu,Shengxiang Gao,Zhenhan Wang,Liuqing Puto develop some of the content through their own examples anThe Subject A little explanation is in order for our choice of the title Linear Opti- 1 mization (and corresponding terminology) for what has traditionally been called Linear Programming.Theword programming in this context can be confusing 作者: 迅速飛過 時間: 2025-3-25 09:38
Yulin Zhang,Chong Feng,Hongzheng Lito develop some of the content through their own examples anThe Subject A little explanation is in order for our choice of the title Linear Opti- 1 mization (and corresponding terminology) for what has traditionally been called Linear Programming.Theword programming in this context can be confusing 作者: 同來核對 時間: 2025-3-25 14:34
Kehai Chen,Rui Wang,Masao Utiyama,Eiichiro Sumitanally been called Linear Programming.Theword programming in this context can be confusing and/or misleading to students. Linear programming problems are referred to as optimization problems but the general term linear p- gramming remains. This can cause people unfamiliar with the subject to think th作者: 榨取 時間: 2025-3-25 19:50 作者: 流出 時間: 2025-3-25 23:15 作者: 手銬 時間: 2025-3-26 01:32 作者: zonules 時間: 2025-3-26 05:13 作者: 使成整體 時間: 2025-3-26 08:53
Improving Bilingual Lexicon Induction on Distant Language Pairs,y, current solutions perform terribly on distant language pairs. To address this problem, we analyze existing models for the lexicon induction task of distant language pairs, such as English-Chinese. We propose an framework for the task with improved preprocessing, mapping and inference accordingly.作者: Receive 時間: 2025-3-26 13:57
Improving Quality Estimation of Machine Translation by Using Pre-trained Language Representation,ll suffers heavily from the problem that the quality annotation data remain expensive and small. In this paper, we focus on overcoming the limitation of QE data and explore to utilize the high level latent features learned by the pre-trained language models to reduce the model’s dependence on QE dat作者: 油膏 時間: 2025-3-26 18:52
Incorporating Syntactic Knowledge in Neural Quality Estimation for Machine Translation, on neural networks have certain capability of implicitly learning the syntactic information from sentence-aligned parallel corpus. However, they still fail to capture the deep structural syntactic details of the sentences. This paper proposes a method that explicitly incorporates source syntax in n作者: ECG769 時間: 2025-3-26 23:41
Independent Fusion of Words and Image for Multimodal Machine Translation, works project the image feature into the text semantic space and merged into the model in different ways. Actually, different source words may capture different visual information. Therefore, we propose a multimodal neural machine translation (MNMT) model that integrates the words and visual inform作者: VAN 時間: 2025-3-27 05:04
Neural Machine Translation with Attention Based on a New Syntactic Branch Distance,ce sentence during translation process. Attention mechanism usually focuses on local attention by using solely the linear index distance of words while ignores syntax structures of sentences. In this paper, we extend local attention through syntax distance constraint, and propose an attention mechan作者: 來這真柔軟 時間: 2025-3-27 06:11 作者: ASSAY 時間: 2025-3-27 11:19 作者: 裂隙 時間: 2025-3-27 14:17 作者: 易于交談 時間: 2025-3-27 21:20 作者: CAND 時間: 2025-3-27 23:10 作者: Anterior 時間: 2025-3-28 03:29 作者: 主動脈 時間: 2025-3-28 08:13
Communications in Computer and Information Sciencehttp://image.papertrans.cn/m/image/620778.jpg作者: Cholesterol 時間: 2025-3-28 12:17 作者: SOBER 時間: 2025-3-28 16:52
,NICT’s Machine Translation Systems for?CCMT-2019 Translation Task,ed the provided parallel data augmented with a large quantity of back-translated monolingual data to train state-of-the-art NMT systems. We then employed techniques that have been proven to be most effective, such as fine-tuning, and model ensembling, to generate the primary submissions of Chinese.English translation tasks.作者: 谷物 時間: 2025-3-28 20:00
Conference proceedings 2019019..The 10 full papers presented in this volume were carefully reviewed and selected from 21 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.作者: Chivalrous 時間: 2025-3-29 00:36
978-981-15-1720-4Springer Nature Singapore Pte Ltd. 2019作者: 預定 時間: 2025-3-29 04:38 作者: 抗原 時間: 2025-3-29 09:58
1865-0929 eptember 2019..The 10 full papers presented in this volume were carefully reviewed and selected from 21 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.978-981-15-1720-4978-981-作者: 手勢 時間: 2025-3-29 13:16 作者: FER 時間: 2025-3-29 16:37 作者: intrude 時間: 2025-3-29 20:33
