554 citations · 605 across the 20 of their papers we have counts for
11 papers · 1 filter
Learning Light-Weight Translation Models from Deep Transformer
Bei Li, Ziyang Wang, Hui Liu +4
Recently, deep models have shown tremendous improvements in neural machine translation (NMT). However, systems of this kind are computationally expensive and memory intensive. In t…
Exploiting Group-level Behavior Pattern forSession-based Recommendation
Ziyang Wang, Wei Wei, Xian-Ling Mao +2
Session-based recommendation (SBR) is a challenging task, which aims to predict users' future interests based on anonymous behavior sequences. Existing methods leverage powerful re…
User-based Network Embedding for Collective Opinion Spammer Detection
Ziyang Wang, Wei Wei, Xian-Ling Mao +3
Due to the huge commercial interests behind online reviews, a tremendousamount of spammers manufacture spam reviews for product reputation manipulation. To further enhance the infl…
Exploring Global Information for Session-based Recommendation
Ziyang Wang, Wei Wei, Gao Cong +4
Session-based recommendation (SBR) is a challenging task, which aims at recommending items based on anonymous behavior sequences. Most existing SBR studies model the user preferenc…
Shallow-to-Deep Training for Neural Machine Translation
Bei Li, Ziyang Wang, Hui Liu +5
Deep encoders have been proven to be effective in improving neural machine translation (NMT) systems, but training an extremely deep encoder is time consuming. Moreover, why deep m…
RAR-U-Net: a Residual Encoder to Attention Decoder by Residual Connections Framework for Spine Segmentation under Noisy Labels
Ziyang Wang, Zhengdong Zhang, Irina Voiculescu
Segmentation algorithms for medical images are widely studied for various clinical and research purposes. In this paper, we propose a new and efficient method for medical image seg…
Weight Distillation: Transferring the Knowledge in Neural Network Parameters
Ye Lin, Yanyang Li, Ziyang Wang +4
Knowledge distillation has been proven to be effective in model acceleration and compression. It allows a small network to learn to generalize in the same way as a large network. R…
Does Multi-Encoder Help? A Case Study on Context-Aware Neural Machine Translation
Bei Li, Hui Liu, Ziyang Wang +5
In encoder-decoder neural models, multiple encoders are in general used to represent the contextual information in addition to the individual sentence. In this paper, we investigat…
A Single RGB Camera Based Gait Analysis with a Mobile Tele-Robot for Healthcare
Ziyang Wang
With the increasing awareness of high-quality life, there is a growing need for health monitoring devices running robust algorithms in home environment. Health monitoring technolog…
A Novel and Efficient Tumor Detection Framework for Pancreatic Cancer via CT Images
Zhengdong Zhang, Shuai Li, Ziyang Wang +1
As Deep Convolutional Neural Networks (DCNNs) have shown robust performance and results in medical image analysis, a number of deep-learning-based tumor detection methods were deve…
Deep Learning in Medical Ultrasound Image Segmentation: a Review
Ziyang Wang
Applying machine learning technologies, especially deep learning, into medical image segmentation is being widely studied because of its state-of-the-art performance and results. I…