论文链接:Neural Machine Translation in Linear Time 标题:Neural Machine Translation in Linear Time 来源:arxiv 作者:deepmind 问题:提出了新型的source--target网络结构ByteNet,并通过两个扩张卷积神经网络(Dilated Convolution)堆叠实现,完成了机器翻译任务,并且将时间复杂度控制在线性范围。 相关工作: 1、扩张卷积...
摘要: Neural machine translation 是用encoder 将源输入编码成固定长度的向量,然后再用decoder解码成目标语言。但是使用固定长度是受限制的,本文就是要提出一种新的机制,让decode的时候可以比较动态的search 源输入。其实也就是attention机制 introduction: 常用的encoder-decoder模式在编码成固定长度的向量时,可能会失去....
Neural machine translation (NMT)Bidirectional LSTMNolinear activation functionNeural machine translation (NMT) has achieved notable achievements in recent years. Although existing models provide reasonable translation performance, they cost too much training time. Especially, when the corpus is enormous, ...
neural machine translation (NMT) systems can leverage highly multilingual capacities and even perform zero-shot translation, delivering promising results in terms of language coverage and quality. However, scaling quality NMT requires large volumes of parallel bilingual data, which are ...
In recent years, the most prominent method is Statistical Machine Translation (SMT; Brown et al. (1993)), which builds a probabilistic model of the target sequence given the source sequenceP(E|F). This probabilistic model is trained using a large set of training data containing pairs of sour...
Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014). Neural Machine Translation (NMT) ● Attention over input sequence ● There’re words in two languages that share the same meaning. ● Attention ⇒ Alignment ○ Differentiable, allowing ...
AP Pentland - 《IEEE Transactions on Pattern Analysis & Machine Intelligence》 被引量: 84发表: 1994年 Sparse calibration of subsurface flow models using nonlinear orthogonal matching pursuit and an iterative stochastic ensemble method We introduce a nonlinear orthogonal matching pursuit (NOMP) for sparse...
Nara Institute of Science and Technology † Language Technologies Institute, Carnegie Mellon University philip.arthur.om0@is.naist.jp gneubig@cs.cmu.edu s-nakamura@is.naist.jp Abstract Neural machine translation (NMT) often makes mistakes in translating low-frequency content words that are essential...
Financial time-series prediction is vital for developing excellent trading strategies in the financial market (Wang, 2014). In past decades, it has attracted much attention from researchers of many fields, especially the Machine Learning community (Lee u. Ready, 1991). These researches mainly focus...
{Nematus: a Toolkit for Neural Machine Translation}, booktitle = {Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics}, month = {April}, year = {2017}, address = {Valencia, Spain}, publisher = {Association ...