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Minimum Risk Training for Neural Machine Translation
TLDR
Experiments show that the proposed minimum risk training approach achieves significant improvements over maximum likelihood estimation on a state-of-the-art neural machine translation system across various languages pairs. Expand
An integrated encyclopedia of DNA elements in the human genome
TLDR
The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research. Expand
Topologically associating domains are stable units of replication-timing regulation
TLDR
It is demonstrated that, collectively, replication domain boundaries share a near one-to-one correlation with TAD boundaries, whereas within a cell type, adjacent TADs that replicate at similar times obscure replicationdomain boundaries, largely accounting for the previously reported lack of alignment. Expand
Robust Neural Machine Translation with Doubly Adversarial Inputs
TLDR
This work proposes an approach to improving the robustness of NMT models, which consists of a gradient-based method to craft adversarial examples informed by the translation loss over the clean inputs. Expand
Towards Robust Neural Machine Translation
TLDR
Experimental results on Chinese-English, English-German and English-French translation tasks show that the proposed approaches can not only achieve significant improvements over strong NMT systems but also improve the robustness of NMT models. Expand
Comparative analysis of regulatory information and circuits across distant species
TLDR
The results suggest that gene-regulatory properties previously observed for individual factors are general principles of metazoan regulation that are remarkably well-preserved despite extensive functional divergence of individual network connections. Expand
Joint Network Optimization and Downlink Beamforming for CoMP Transmissions Using Mixed Integer Conic Programming
TLDR
This paper considers the problem of joint network optimization and downlink beamforming (JNOB), with the objective to minimize the overall BS power consumption (including the operational costs of CoMP transmission) while guaranteeing the quality-of-service (QoS) requirements of the mobile stations (MSs). Expand
Semi-Supervised Learning for Neural Machine Translation
TLDR
This work proposes a semi-supervised approach for training NMT models on the concatenation of labeled and unlabeled monolingual corpora data, in which the source- to-target and target-to-source translation models serve as the encoder and decoder, respectively. Expand
A Teacher-Student Framework for Zero-Resource Neural Machine Translation
TLDR
This paper proposes a method for zero-resource NMT by assuming that parallel sentences have close probabilities of generating a sentence in a third language, and is able to train a source-to-target NMT model without parallel corpora available. Expand
Comments on "Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering"
TLDR
Experimental results demonstrate that the proposed modification achieves better results in terms of both peak signal-to-noise ratio and subjective visual quality than the original method for strong noise. Expand
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